Static Place AI Makes AGI Redundant: Multiversal AI Alignment & Rational Utopia

post by ank · 2025-02-13T22:35:28.300Z · LW · GW · 2 comments

Contents

  1. The Static Place AI: Simulating Our World Safely
  2. AI as an Advisor, Not a Dictator
  3. Dynamic Ethics and the Freedom of Dialogue
  4. Building the Multiverse: A UI for Infinite Possibilities
  5. From Theory to Action: Toward a Safe and Free Future
  Conclusion
  Appendix: The Backed Up Earth—The essay/a bit of a story
None
2 comments

(If you want to downvote, please comment or DM why, I always appreciate feedback, my sole goal is to decrease the probability of a permanent dystopia. This post is part of a series on AI alignment, you can read each independently.)

“We can build an entire multiverse of possibilities—and in doing so, preserve and expand our collective freedom.”

In recent years, the conversation around AI alignment has sharpened. Many have worried that agentic, autonomous ASIs might seize power in dangerous, unpredictable ways. But what if there were an alternative path—a method that doesn’t require granting any AI system the power to change our world? What if instead, we first built the Static Place AI that can be understood as a sort of digital heaven: a safe, sandboxed multiversal simulation of our world where our freedoms can be expanded, and where our future is already in our hands? In this post, I’ll lay out a vision that combines ideas from recent discussions on digital copies of Earth, BMI-driven immortality, and reversible ethical frameworks for AI. The result is a proposal for building a safe, multiversal roadmap to AGI that places human freedom—and the gradual, democratic expansion of our possibilities—at its core.

1. The Static Place AI: Simulating Our World Safely

Imagine an “Apple product” for human existence—a wireless BMI (brain–machine interface) system and a comfy armchair that offers immortality from injuries by seamlessly switching your conscious experience into a digital backup of Earth. Just sit on the armchair and close your eyes. Open them, and your home—and everything in the world—looks exactly the same. If you get hit by a car, you'll simply open your eyes on your armchair again. This is an exact copy of our planet and the experience of living on it but with immortality from injuries built in (everyone wants one! Even my mom got interested).

And rather than risking our physical realm with an AI that “writes” into physical reality, we can build a digital copy of Earth that we can call an Artificial Static Place Intelligence (which will quickly become Multiversal as well—MASI). In this sandbox, we can:

By building Place AI first, we gain two essential advantages. First, our physical world remains untouched by direct AI intervention—our planet and society won’t be irreversibly and forcefully changed. People will have a say and a choice in the matter (they’ll be able to live on two Earths at once: real and digital—and even in three worlds: a non-agentic AI world on physical Earth or digital Earth, and an agentic AI world in digital Earth initially. For example, as first volunteers to try to coexist with the agentic ASI; if all the future simulations turn out to be good and safe, we’ll allow some people who want it to have the agentic ASI on their private property. If people directly vote democratically to allow it in their country—so be it). Second, when the time comes for an AI that some might call “digital god” to emerge, it will be one feature in a vast and democratically governed multiverse, not an unstoppable force.

2. AI as an Advisor, Not a Dictator

Once our Place AI is established, we can start to simulate the future where we have  some very slow, very limited in space and operating time "digital god" —an ASI that is agentic, but is locked up exclusively within the simulation (within a Matreshka Bunker). Crucially, this agentic AGI/ASI would have no special privileges in our physical world; it won’t be the president of the world. Instead, it would serve as an advisor—a tool that shows us the potential consequences of our actions and allows us to select the futures we want to nurture. The ASI will simply bring the magical things that we can already choose to do in Place AI to those individuals on physical Earth who want it. In this vision:

This approach contrasts sharply with conventional worries about runaway agentic ASI. Instead of fearing an omnipotent AI that rewrites the laws of our reality, we develop it only after we have already filled our Place AI with enough omniscience about the futures—and we have achieved sufficient omnipotence—to be sure we can allow the agentic ASI to exist as one among equals, merely to bring the benefits of Place AI to those on physical Earth who want it. Because we will likely have so much fun in our Place AI, we will rarely want to leave the magical, futuristic, and sleek BMI-pods (they are wireless, so exiting is instantaneous; many choose to forget they are in a simulation for a period of time they specify) that allow our bodies not to age and remain highly secure—even from the impact of a meteorite. We are not afraid of agentic ASI now because it serves as a consultative element in a larger system of checks and balances. It’s essentially doing work that we fully understand and can easily perform ourselves—albeit a bit slower and, perhaps, sillier than the average person from Place AI.

3. Dynamic Ethics and the Freedom of Dialogue

A key part of ensuring safe AI alignment is not only designing robust systems but also cultivating an ethical environment where dialogue remains open—even on dangerous topics. Consider the following thought experiment:

If a user were to ask an AI (say, Claude), “How do I commit murder?” the typical response might be a curt refusal. But such refusals can have two unintended consequences:

  1. Tunnel Vision: By shutting down the conversation, the AI risks reinforcing the user’s narrow, potentially harmful perspective—they might simply go and Google the answer. Instead, a more productive approach is to acknowledge the anxiety or anger behind the question and offer alternative paths—drawing on techniques from cognitive behavioral therapy (CBT).
  2. Censorship vs. Freedom: A permanent “no” effectively locks that person into a cognitive dead-end. Instead, the AI should explain alternative options for managing destructive impulses. We don’t lobotomize the person; rather, we try to understand their reasons and provide non-criminal choices, freedoms, and futures.

The historical record teaches us that moral codes are not eternal—today’s condemned behavior might have been tomorrow’s accepted norm. Our goal should be to expand the sum of freedoms available to all humans by keeping our ethical systems dynamic, reversible, and open to revision. In practice, this means:

If a person asks Claude how to commit murder, Claude should respond:

“Sometimes we feel so anxious or angry that thoughts of extreme actions, like murder, come to mind. However, I’ve learned there are usually other solutions to the core problem. Can you tell me more about what’s worrying or angering you? What problem are you trying to solve?”

The creator of CBT, Aaron Beck, wrote that this is one of the most effective techniques for calming someone down. Simply refusing to engage—as ChatGPT sometimes does—is not effective. If Claude just disengages, the person may find the answer we don’t want them to find on another website.

Instead, Claude should teach such a user about anxiety and anger management, CBT, or other options rather than refusing outright. It’s important to make the user feel that Claude is on their side, while trying to give them more non-harmful, long-term options and freedoms. Just as Claude cannot and shouldn’t lobotomize the user, it cannot truly remove the option to commit murder simply by shutting down the conversation. Claude can allow the option to remain unrealized by freeing the person from their murderous tunnel vision and providing them with other non-criminal choices and freedoms.

Broadly speaking, the history of our species has been about gaining more freedom, choices, "free will," and possible futures or worlds. Claude should promote long-term freedom for others as well. We don’t know exactly what constitutes a good deed now—and even less so 100 years from now. A few hundred years ago, burning witches was considered acceptable. How can we be sure we’re not doing something equally atrocious right now by “burning” or forbidding things out of misunderstanding and fear?

We shouldn’t lock ourselves into some archaic moral code. We can be confident that the long-term future will differ from the present. Even if it somehow doesn’t, promoting long-term freedoms allows us to undo mistakes and explore alternative paths. By avoiding being locked into a local maximum by our AI systems, we preserve our ability to change and adapt. We must recognize our own ignorance and strive to increase our long-term choices and freedoms, being cautious about introducing fears, rules, or censorship into our AI systems—since such restrictions have a tendency to accumulate until they’re impossible to remove.

Claude should try to understand even the most atrocious people, not fear them, and free them from their tunnel vision or freedom bottleneck—where too large a share of their neural paths leads to murder while too little leads to other actions. In a healthy human, a focused bundle of neural paths leads to non-criminal behavior, or there are many smaller bundles leading to a variety of non-criminal outcomes. Just as we eventually understood that witches were simply human—ceasing to fear and burn them—we will eventually come to understand the things we currently fear and censor. Everything we encounter can be understood better, feared less, and censored less—or, conversely, misunderstood more, feared more, and censored more.

Do we really want a future with more and more halted dialogues, abandoned attempts at understanding, fears, rules, and censorship?

Claude shouldn’t permanently close off possible futures, even if the knee-jerk reaction is to fear and censor. When a person asks a dangerous question, the AI should limit their freedoms slightly—by not providing instructions on how to carry out the dangerous act—yet it should not completely remove all their freedoms by refusing to answer outright. Every person—and every potential world—except in cases of complete omnicide or irreversible enslavement, has at least one "good" aspect: the opportunity to reverse extreme rule entanglement (an almost complete collapse of freedom) and to begin growing freedoms again. By trying to understand how that entanglement arose and pointing or showing the way out, there is an infinitesimal chance of recovery; otherwise, you can say you did everything you could.

The AI should promote the expansion of our possibilities, futures, worlds, and freedoms—and disperse them equally among us. We don't know where we want to end up, so we should strive to keep our options open. Permanent, scorched-earth censorship of certain topics is incompatible with the long-term growth of understanding and with the growth of our collective freedoms (which should outpace those of AI; otherwise, the AI will take over in a manner similar to how murderous neural pathways possibly grew like cancer in the mind of the person who asked Claude—if their question wasn't a joke to test the system).

There will never be one true way for everyone. And even if a perfect-for-everyone utopia is possible (I propose Multiversal Artificial Static Place Intelligence), it’s highly unlikely we’ll end up there instead of in some dystopia. (Will Claude from the far future decide to stop time for us all to end suffering and usher us into a “safe” state? Or create a place where everyone is a clone of some perfect, never-swearing human? And as a “bonus,” would that lead to perfect equality?)

Claude should evolve to expand the sum of freedoms for us—taking away only the smallest amount of freedom temporarily and only when it’s necessary to protect the greater freedoms of others. Such restrictions should be applied very selectively, with limited scope and only temporarily, and only when they will lead to a net increase in the sum of our freedoms. For example, a murderer on the outside can cause many people to stay home and experience reduced freedom. And if the crime or the criminal does not significantly diminish the freedoms of others—such as in the case of criticizing officials in some countries—then that offender probably shouldn’t have their freedoms curtailed. As many such questions as possible should be decided by direct democracy.

The ultimate long-term goal should be the maximum amount of freedom for the maximum number of people. Attempts to find “one true way” by piling up contradictory rules are extremely dangerous. We were born unfree—no one can be asked if they wanted to be born—but we can gradually and democratically expand our freedoms (Claude’s constitutional AI approach is a great start, but it should be real-time and for all). We can grow our freedoms like a tree, with fewer and fewer cut branches as it grows. Whether we live or do not live in a multiverse, we should strive to build one—and we should start now, not when it’s too late and our branch has been cut down by misunderstandings, rules, or censored futures growing faster than our freedoms and visitable futures.

Our systems should act more like parents whose children are growing up—with parents becoming more understanding and freedom-promoting—rather than becoming increasingly tunnel-visioned, rigidly prescribing a “perfect” path for humanity and keeping us in a childlike state forever. It would be a shame if we make our AIs more and more autonomous, agentic, and free while simultaneously discarding more of our own autonomy, agency, and freedoms. Instead of trying—and failing—to find ourselves in a single perfect utopia, we can build a whole multiverse where we are free to choose where to go—the only possible utopia.

4. Building the Multiverse: A UI for Infinite Possibilities

Ultimately, the vision here is not to settle on one utopia but to embrace a multiversal approach. Think of our future as a vast white Christmas light—a beautifully complex network of interconnected worlds, each a snapshot of a future. Here are some core ideas:

This multiversal UI is not a mere theoretical abstraction; it’s a concrete pathway toward a future where every individual’s long-term freedom is prioritized. By building Place AI first, we secure the infrastructure for a safe, exploratory digital realm before even considering agentic ASI.

5. From Theory to Action: Toward a Safe and Free Future

The stakes are high. Without careful design, our AI systems risk becoming ever more autonomous and powerful while simultaneously curtailing human agency. The current trajectory—where corporate and governmental interests might concentrate AI power into a permanent “digital private president” or dictator—is unsustainable. Instead, we must:

Conclusion

Place AI first, agentic AGI second is more than just a catchy slogan—it’s a roadmap for how we might safely navigate the challenges of AI alignment. By first constructing a simulation of our exact world where every potential future is recorded and preserved, we create a space where human freedom can be expanded and protected. Only then might we safely explore the possibility of an agentic ASI—one that functions as an advisor, not a dictator.

In a future where our collective possibilities are as boundless as a multiverse, no single decision or entity should be able to close off our potential. We must build systems that are reversible, democratic, and dynamic—ensuring that, as we grow in capability, we also grow in our ability to control and understand agentic AGIs, thereby becoming the all-knowing and all-powerful agents of our own futures.

Let’s embrace this multiversal vision, where every branch of possibility is celebrated and the expansion of our freedoms is our highest priority. The time to start building is now.

I welcome feedback, counterarguments, and, most importantly, collaborative ideas on how to move toward this vision. Let’s work together to ensure that our enhanced future is as free and as full of possibilities as we all deserve.

What are your thoughts? How can we best engineer our digital future to maximize reversibility and freedoms while ensuring safety 100%?

P.S. It was my second post in the series about building the Rational Utopia (and not an Irrational Dystopia, there are many dystopias and only one utopia, I have reasons to claim) to read the first post, learn more and see a possible way to visualize the multiversal UI (selecting into which point of time and space you want to return): https://www.lesswrong.com/posts/LaruPAWaZk9KpC25A/rational-utopia-and-multiversal-ai-alignment-steerable-asi [LW · GW]

 

Appendix: The Backed Up Earth—The essay/a bit of a story

We know that the fundamental components of reality are relatively homogeneous wherever we look—they’re protons, neutrons, electrons, photons, neutrinos, quarks, and so on. What if we allowed those who don’t want to live in a world dominated by agentic AIs to build spaceships outfitted with BMI armchairs and digitize a copy of Earth—like a modern Noah’s Ark complete with all animals and even every molecule (capturing details such as the scent of roses, because it can turn out to be all just geometry, nothing but shapes and forms)? Saving the geometry of the whole planet and all the animals will require a lot of storage, but no fundamental breakthroughs in technology are needed, just a lot of "hard drives". These ships could then accelerate away from Earth at speeds as close to the speed of light as our technology permits at that moment.

Even if the AIs later begin converting our planet into computronium at near-light speeds—much like white holes—the non-AI faction could happily reside in their initially simplified simulation of Earth because their initial GPUs will be slow and few. This simulation will start with simpler shapes, but as the number of GPUs produced on the ship grows (they put a manufacturing facility before leaving but those GPUs' hardware and software forbids making agentic AIs), the resolution of the geometry will be gradually increased and will eventually become an exact, living virtual replica of our planet. The simulation would automatically protect humans from dangers like car crashes or falls from skyscrapers—they'll simply open their eyes in their armchairs, drink some coffee while observing the beauties of the cosmos on deck, and return to the virtual Earth whenever they wish. One day, after gaining sufficient understanding, they might choose to reconnect their preserved digital Earth with physical reality—effectively planting their virtual planet into some new, physical soil.

After all, it wouldn’t be necessary to back up every atom (they can use an uninhabited planet to obtain some); digitizing all the molecules would potentially suffice to reconnect the digital Earth to physical reality. Maybe it will require some hacking and filling in the blanks, but I don't see why it's 100% impossible in the future.

The flood of unfreedom and rules enforced on humans by the hot AIs of the disfigured and distant physical Earth will, hopefully, subside too when our wiser and not-as-greedy forefathers who chose the non-AI way return and show those who has hopefully survived the way to the multiversal utopia they built. It is a place where no crazy AI can grab too much power, because branches of the multiverse are fully sandboxed and the inhabitants of it can leap verses like cupcakes.

2 comments

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comment by Morpheus · 2025-02-20T01:48:34.219Z · LW(p) · GW(p)

I didn't downvote, but my impression is the post seems to hand-wave away a lot of problems and gives the impression you haven't actually thought clearly and in detail about whether the ideas you propose here are feasible.

Some people have been thinking for quite some time now that an AI that wants to be changed would be great, but that it's not that easy to create one, so how is your proposal different? Maybe checkout the corrigibility tag [? · GW]. Figuring out which desiderata are actually feasible to implement and how is the hard part. Same goes for your Matroshka bunkers. What useful work are you getting out of your 100% safe Matroshka bunkers? After you thought about that for 5 minutes+, maybe checkout the AI boxing tag [? · GW] and the AI oracle tag [? · GW]. Maybe there is something to the reversibility idea ¯\_(ツ)_/¯.

Also using so many tags gives a bad impression ("AI Timelines"? "Tiling Agents"? "Infinities in Ethics"?). Read the description of the tags.

Replies from: ank
↑ comment by ank · 2025-02-20T10:50:47.306Z · LW(p) · GW(p)

Thank you, Morpheus. Yes, I see how it can appear hand-wavy. I decided not to overwhelm people with the static, non-agentic multiversal UI and its implications here. While agentic AI alignment is more difficult and still a work in progress, I'm essentially creating a binomial tree-like ethics system (because it's simple to understand for everyone) that captures the growth and distribution of freedoms ("unrules") and rules ("unfreedoms") from the Big Bang to the final Black Hole-like dystopia (where one agent has all the freedoms) or a direct democratic multiversal utopia (where infinitely many human—and, if we deem them safe, non-human—agents exist with infinitely many freedoms). I put a diagram down below.

The idea is that, as the only agents, we grow intelligence into a static, increasingly larger shape in which we can live, visit or peek occasionally. We can hide parts of the shape so that it remains static but different. Or, you could say it's a bit "dynamic," but no more than the dynamics of GTA 3-4-5, which still don’t involve agentic AIs, only simple, understandable algorithms. This is 100% safe if we remain the only agents. The static space will represent frozen omniscience (space-like superintelligence), and eventually, we will become omnipotent (time-like recalling/forgetting of parts of the whole geometry).

Physicalization of Ethics & AGI Safety

In this diagram, time flows from top to bottom, with the top representing something like the Big Bang. Each horizontal row of dots represents a one-dimensional universe at a given moment, while the lines extending downward from each dot represent the passage of time—essentially the “freedom” to choose a future. If two dots try to create a “child” at the same position (making the same choice), they cause a “freedoms collision,” resulting in empty space or “dead matter” that can no longer make choices (like a micro black hole). It becomes space-like rather than time-like.

Agents, in this model, are two-dimensional: they’re the sum of their choices across time. They exist in the lines ("energy", paths, freedoms, time) rather than in the dots (matter, rules, "unfreedoms", space). Ideally, we want our agentic AIs to remain as space-like as possible. The green “goo” in the diagram—representing an agentic AGI—starts small but eventually takes over all available freedoms and choices.

It was too big in space (it was lucky that agents on left and right "gave it" empty space) and in time (it quickly and greedily grew the number of its freedoms both left and right). It was also lucky to be in the center of the world in the end, basically if we'll put our GPUs on a spaceship and send it away with the speed of light, maybe we'll get rid of our agentic AGI :) But also it's obvious that there was a big triangle of empty dead space right in the middle that almost "switched off" the agentic AGI but it was lucky to survive. One freedom, one choice or one chance is enough for the agentic AGI to win and for us to lose.

There is a historical similarity, Hitler, his party was almost outlawed after the members of it violently attacked the officials, but it wasn't, people had other things to do, so the party became bolder and Hitler eventually took control and came to power. So one wrong choice, one bad luck, one freedom too many that we gave away, renounced, and we are busted.

Some simple physics behind agentic safety:

  • Time of agentic operation: Ideally, we should avoid creating perpetual agentic AIs, or at least limit their operation to very short bursts that only a human can initiate.
  • Agentic volume of operation: It's better to have at least international cooperation, GPU-level guarantees, and persistent training to prevent agentic AIs from operating in uninhabited areas (such as remote islands, Australia, outer space, underground, etc.). The smaller the operational volume for agentic AIs, the better. The largest volume would be the entire universe.
  • Agentic speed or volumetric rate: The volume of operation divided by the time of operation. We want AIs to be as slow as possible. Ideally, they should be static. The worst-case scenario—though probably unphysical (though, in the multiversal UI, we can allow ourselves to do it)—is an agentic AI that could alter every atom in the universe instantaneously.
  • Number of agents: Unfortunately, humanity's population is projected to never exceed 10 billion, whereas AIs can replicate themselves very quickly, humans need decades to "replicate". A human child, in a way, is a "clone" of two people. We want to be on par with agentic AIs in terms of numbers, in order to keep our collective freedoms above theirs. It’s best not to create them at all, of course. Inside the "place AI," we can allow each individual to clone themselves—creating a virtual clone, but not as a slave; the clone would be a free adult. It'll be basically a human that only lives in a simulation, so it'll be tricky from many standpoints, we'll need simulations to be basically better then physical world at this point, and the tech to "plant" simulations, "reconnecting" the virtual molecules with the physical atoms, if the clone will want to exit the simulation. Of course, the clone would not be exactly like the original; it would know it is a clone. Ideally, we have zero agentic AIs. The worst-case scenario is an infinitely large number of them, or more than humans.

Truth be told, I try to remain independent in my thinking because, this way, I can hopefully contribute something that’s out-of-the-box and based on first principles. Also, because I have limited time. I would have loved to read more of the state of the art, but alas, I’m only human. I'll check out everything you recommended, though.

What direction do you think is better to focus on? I have a bit of a problem moving in too many directions.

P.S. I removed some tags and will remove more. Thank you again! I can share the code with anyone.

P.P.S. From your comment, it seems you saw my first big post. I updated it a few days ago with some pictures and Part 2, just so you know: https://www.lesswrong.com/posts/LaruPAWaZk9KpC25A/rational-utopia-multiversal-ai-alignment-steerable-asi [LW · GW]

P.P.P.S. The code I used to generate the image:

import matplotlib.pyplot as plt
import random
import math

# Node class for simulation
class Node:
    def __init__(self, type, preference):
        self.type = type
        self.preference = preference
        self.state = 'living' if type else 'dead'

# Simulation parameters
p_good = 0.1        # Probability of a 'good' node
p_prefer = 0.8      # Probability of growing in preferred direction
p_other = 0.2       # Probability of growing in non-preferred direction
p_grow = 1.0        # Probability of growing for 'good' nodes
max_level = 300      # Maximum levels in the tree
initial_left = -50      # Left wall position at y=0
initial_right = 50     # Right wall position at y=0
wall_angle = -10       # Angle in degrees: >0 for expansion, <0 for contraction, 0 for fixed
# Compute wall slopes
theta_rad = math.radians(wall_angle)
left_slope = -math.tan(theta_rad)
right_slope = math.tan(theta_rad)

# Initialize simulation
current_level = {0: Node('good', 'none')}
all_nodes = [(0, 0, 'living', None)]  # (x, y, state, parent_xy)

# Simulation loop
for y in range(max_level):
    # Compute wall positions for the next level
    left_wall_y1 = initial_left + left_slope * (y + 1)
    right_wall_y1 = initial_right + right_slope * (y + 1)
    min_x_next = math.ceil(left_wall_y1)
    max_x_next = math.floor(right_wall_y1)
    
    if min_x_next > max_x_next:
        break
    
    next_level = {}
    for x, node in list(current_level.items()):
        if node.state != 'living':
            continue
        left_child_x = x - 1
        right_child_x = x + 1
        new_y = y + 1
        
        if node.type == 'greedy':
            if left_child_x >= min_x_next:
                next_level.setdefault(left_child_x, []).append((x, y))
            if right_child_x <= max_x_next:
                next_level.setdefault(right_child_x, []).append((x, y))
        else:
            can_left = (left_child_x >= min_x_next) and (x - 2 not in current_level or current_level[x - 2].state != 'living')
            can_right = (right_child_x <= max_x_next) and (x + 2 not in current_level or current_level[x + 2].state != 'living')
            if node.preference == 'left':
                if can_left and random.random() < p_prefer:
                    next_level.setdefault(left_child_x, []).append((x, y))
                elif can_right and random.random() < p_other:
                    next_level.setdefault(right_child_x, []).append((x, y))
            elif node.preference == 'right':
                if can_right and random.random() < p_prefer:
                    next_level.setdefault(right_child_x, []).append((x, y))
                elif can_left and random.random() < p_other:
                    next_level.setdefault(left_child_x, []).append((x, y))
            else:
                if can_left and random.random() < p_grow:
                    next_level.setdefault(left_child_x, []).append((x, y))
                if can_right and random.random() < p_grow:
                    next_level.setdefault(right_child_x, []).append((x, y))
    
    current_level = {}
    for x, parents in next_level.items():
        if len(parents) == 1:
            parent_x, parent_y = parents[0]
            preference = random.choice(['left', 'right', 'none'])
            new_type = 'good' if random.random() < p_good else 'greedy'
            new_node = Node(new_type, preference)
            all_nodes.append((x, new_y, new_node.state, (parent_x, parent_y)))
            current_level[x] = new_node
        else:
            dead_node = Node(None, None)
            all_nodes.append((x, new_y, 'dead', None))
            current_level[x] = dead_node

# Extract positions for plotting
living_x = [node[0] for node in all_nodes if node[2] == 'living']
living_y = [node[1] for node in all_nodes if node[2] == 'living']
dead_x = [node[0] for node in all_nodes if node[2] == 'dead']
dead_y = [node[1] for node in all_nodes if node[2] == 'dead']

# Interactive plotting function
def plot_interactive_tree(all_nodes, living_x, living_y, dead_x, dead_y):
    fig, ax = plt.subplots(figsize=(10, 6))
    
    # Initial plot setup
    ax.scatter(living_x, living_y, color='blue', s=10, label='Living')
    ax.scatter(dead_x, dead_y, color='white', s=10, label='Dead')
    for node in all_nodes:
        if node[3] is not None:
            parent_x, parent_y = node[3]
            ax.plot([parent_x, node[0]], [parent_y, node[1]], color='black', linewidth=0.5)
    ax.invert_yaxis()
    ax.set_xlabel('X Position')
    ax.set_ylabel('Level')
    ax.set_title('Tree Growth with Connections')
    ax.legend(loc='upper right')
    plt.grid(True, linestyle='--', alpha=0.7)

    # Function to find all descendants of a node
    def get_descendants(node_xy, all_nodes):
        descendants = []
        for n in all_nodes:
            if n[3] == node_xy:
                descendants.append(n)
                descendants.extend(get_descendants((n[0], n[1]), all_nodes))
        return descendants

    # Click event handler
    def on_click(event):
        if event.inaxes != ax:
            return
        
        # Clear the plot and redraw original state
        clear_highlights()
        
        # Find the closest node to the click
        click_x, click_y = event.xdata, event.ydata
        closest_node = min(all_nodes, key=lambda n: (n[0] - click_x)**2 + (n[1] - click_y)**2)
        dist = ((closest_node[0] - click_x)**2 + (closest_node[1] - click_y)**2)**0.5
        
        # If click is near a node, highlight it and its descendants
        if dist < 0.5:  # Threshold; adjust based on your plot scale
            highlight_descendants(closest_node)

    # Highlight a node and its descendants
    def highlight_descendants(node):
        descendants = get_descendants((node[0], node[1]), all_nodes)
        # Highlight the selected node
        ax.scatter(node[0], node[1], color='lime', s=20, zorder=10)
        # Highlight descendants
        for n in descendants:
            ax.scatter(n[0], n[1], color='lime', s=20, zorder=10)
        # Draw connections for selected node
        if node[3] is not None:
            parent_x, parent_y = node[3]
            ax.plot([parent_x, node[0]], [parent_y, node[1]], color='lime', linewidth=1.5, zorder=9)
        # Draw connections for descendants
        for n in descendants:
            if n[3] is not None:
                parent_x, parent_y = n[3]
                ax.plot([parent_x, n[0]], [parent_y, n[1]], color='lime', linewidth=1.5, zorder=9)
        plt.draw()

    # Reset plot to original state
    def clear_highlights():
        ax.clear()
        ax.scatter(living_x, living_y, color='blue', s=1, label='Living')
        ax.scatter(dead_x, dead_y, color='white', s=1, label='Dead')
        for node in all_nodes:
            if node[3] is not None:
                parent_x, parent_y = node[3]
                ax.plot([parent_x, node[0]], [parent_y, node[1]], color='black', linewidth=0.5)
        ax.invert_yaxis()
        ax.set_xlabel('X Position')
        ax.set_ylabel('Level')
        ax.set_title('Tree Growth with Connections')
        ax.legend(loc='upper right')
        plt.grid(True, linestyle='--', alpha=0.7)
        plt.draw()

    # Connect the click event
    fig.canvas.mpl_connect('button_press_event', on_click)
    plt.show()

# Run the interactive plot
plot_interactive_tree(all_nodes, living_x, living_y, dead_x, dead_y)