Questions tagged [multi-agent-systems]

For questions related to multi-agent systems (MAS), which are systems that involve multiple agents (each of them can have different skills) that cooperate with each other and interact with the environment. There are several challenges faced by MAS, including coordination between agents, security, and task allocation. Multi-agent systems have been applied in areas such as computer science, civil engineering, and electrical engineering.

Filter by
Sorted by
Tagged with
1 vote
0 answers
52 views

Has anyone here tried to implement MADDPG for a different environment and succeeded?

Has anyone tried implementing the multi-agent RL algorithm MADDPG (I've linked the paper below)? The paper seems to have a good amount citations, and they do have their code on github. However, a few ...
  • 111
0 votes
0 answers
21 views

How can I keep markov property when controlling many agents?

I am working on a project in which I am training a multiagent system to find a minimum in a scalar field. I have many agents that will receive information about the position of some of the other ...
0 votes
0 answers
11 views

Question about definitions of "regret" and "no-regret learning rule" in "Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations"

let $\alpha^t$ be the average per-period reward the agent received up until time $t$, and let $\alpha^t(s_i)$ be the average per-period reward the agent would have received up until time $t$ had he ...
1 vote
1 answer
77 views

How can rewards and loss calculation be extended to multiple agents in a vanilla policy gradient RL setting?

Say I have a simple multi-agent reinforcement learning problem using vanilla policy gradient methods (i.e. REINFORCE) that is currently running with one network per agent. If I can say that each of my ...
  • 89
0 votes
0 answers
24 views

Why does providing an extra prediction output help stabilize training?

I am reading the PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning paper where they tackle the multi-agent path finding problem using reinforcement learning. The problem is ...
0 votes
0 answers
95 views

Agent communication in multi agent system

My task is to compare different ways of communication between two(or more) intelligent agents and decide which has the best performance. I've done my research, and it appears that there are two ways ...
  • 1
0 votes
0 answers
27 views

Are there assumptions made about Self-Play that don't hold up in regular MA competition?

I read about this paper Efficient Competitive Self-Play Policy Optimization which proposes an algorithm for training a population of agents with self-play using a perturbation based matchmaking ...
  • 115
1 vote
0 answers
43 views

Book/course recommendation on game theory application to multi-agent system (reinforcement learning)

Is there any great game theory book or course that discusses the application of game theory to modern reinforcement learning or multi-agent systems? Or a classic reference book that can help me get a ...
  • 431
0 votes
1 answer
131 views

Can a Reinforcement Learning problem with multiple simultaneous actions be formalized as a Multiagent Partially Observable Markov Decision Process?

Consider the following decision making problem. We have a controller that selects locations from a grid of coordinates and captures an image (observation $o_t$) with a camera at each location (action $...
1 vote
0 answers
155 views

How to parallelize multi-agent DDPG (MADDPG)

I am experimenting with MADDPG algorithm implemented in this repo. Since there were only a few agents (2-3) in the implementation (also in the original paper) steps like parameter updates, action ...
  • 331
0 votes
1 answer
85 views

How to implement a rule-based decision maker for an agent-based model?

I had no idea that there is a stack exchange community for A.I. :-/ So I repost this question here in hope of some guidelines. I tried to delve into the materials discussed in AI: A Modern Approach ...
1 vote
0 answers
217 views

RLLib - What exactly do the avail_action and action_embed_size represent? How do they work with the action_mask to phase out invalid actions?

So, I'm fairly new to reinforcement learning and I needed some help/explanations as to what the action_mask and avail_action fields alongside the action_embed_size actually mean in RLlib (the ...
0 votes
0 answers
413 views

RLlib's Multi-agent PPO continuous actions turn into nan

After some amount of training on a custom Multi-agent sparse-reward environment using RLlib's (1.4.0) PPO network, I found that my continuous actions turn into nan (explodes?) which is probably caused ...
  • 223
-1 votes
1 answer
405 views

Policy Gradient ( Advantage actor-critic) for multiple simultaneous continuous actions

i'm trying to solve a problem in which i need to carry out reinforcement learning with multiple simultaneous actions in continuous action space . i checked the multiagent structure; however, im trying ...
1 vote
0 answers
39 views

Why is the number of examined nodes $ O(b^{3d/4})$ in $\alpha$-$\beta$ pruning?

I'm taking a course 'Introduction to AI' and, in one of the tutorials, it was written that when pruning the game tree using $\alpha$-$\beta$ boundaries, the number of nodes that will be developed, ...
3 votes
3 answers
677 views

Why does Alpha Zero's Neural Network flip the board to be oriented towards the current player?

While reading the AlphaZero paper in preparation to code my own RL algorithm to play Chess decently well, I saw that the "The board is oriented to the perspective of the current player." I ...
5 votes
1 answer
910 views

How does the Alpha Zero's move encoding work?

I am a beginner in AI. I'm trying to train a multi-agent RL algorithm to play chess. One issue that I ran into was representing the action space (legal moves/or honestly just moves in general) ...
1 vote
0 answers
26 views

How would I design a finite budget, cascaded multi agent deep reinforcement learning model?

In most of the multi-agent reinforcement learning models I've found, it seems to generate the observations for each of the agents simultaneously and then uses a centralized critic to assess all of the ...
  • 111
2 votes
0 answers
66 views

What place do Agent Communications Language have in Multi-Agent Systems nowadays?

I am currently working on implementing a Multi-Agent System for Smart Grids. There's a lot of literature for that and some things confuse me. I have read that there is FIPA, which aimed to create a ...
2 votes
1 answer
83 views

Is there multi-agent reinforcement learning model in which (some of the) reward is given by other agent and not by the external environment?

The traditional setting of multiagent reinforcement learning (MARL) is the mode in which there is set of agents and external environment. And the reward is given to each agent - individually or ...
  • 803
2 votes
0 answers
396 views

Designing Policy-Network for Deep-RL with Large, Variable Action Space

I am attempting a project involving training an agent to play a game using deep reinforcement learning. This project has a few features that complicate the design of the neural network: The action ...
0 votes
1 answer
143 views

How to train the NN of simple agents given a reward system?

I'm not an expert in AI or NN, I gathered most of the information I have from the internet, and I'm looking for advice and guidance. I'm trying to design a NN that is going to be used by all the ...
  • 109
0 votes
1 answer
630 views

How to handle a changing in the Reinforcement Learning environment where there is increasing or decreasing in number of agents?

I'm working in A2C and I have an environment where there is increasing or decreasing in the number of agents. The action space in the environment will not change but the state will change when new ...
3 votes
1 answer
241 views

Can AlphaZero considered as Multi-Agent Deep Reinforcement Learning?

Can AlphaZero considered as Multi-Agent Deep Reinforcement Learning? I could not find a clear answer on this. I would say yes it is Multi Agent Learning, as there are two Agents playing against each ...
  • 33
1 vote
1 answer
101 views

What is the relation between multi-agent learning and reinforcement learning?

What is the relation between multi-agent learning and reinforcement learning? Is one a sub-field of the other? For instance, would it make sense to state that your research interest are multi-agent ...
  • 175
2 votes
0 answers
90 views

How does heuristic work with multiple agents?

I have a question for heuristic search with multiple agents. I know how heuristic search works with one agent (ex. one Pacman) but I don't really understand it with multiple agents. Let's say we have ...
  • 121
1 vote
1 answer
200 views

Shouldn't the utility function of two-player zero-sum games be in the range $[-1, 1]$?

In Appendix B of MuZero, they say In two-player zero-sum games the value functions are assumed to be bounded within the $[0, 1]$ interval. I'm confused about the boundary: Shouldn't the value/...
  • 431
1 vote
0 answers
24 views

Are there any board game appropriate to examine the performance of multiple agents that cooperate both inter-group and intra-group?

I want to find out scenarios that useful to examine the performance of intra-group and inter-group cooperation in MARL. Specifically, I prefer a board game (like sudoku) that is suitable for the ...
  • 41
1 vote
0 answers
34 views

Do I need to maintain a separate population in each distributed environment when implementing PBT in a MARL context?

I have questions regarding on how to implement PBT as described in Algorithm 1 (on page 5) in the paper, Population Based Training of Neural Networks to train agents in a MARL (multi-agent ...
  • 161
2 votes
1 answer
98 views

Agents meeting in a directed connected graph

We have a directed connected graph, where nodes are places one can go to and edges are the "roads" between places. We have K agents whose goal is to meet in one node. Agents start in ...
  • 161
1 vote
2 answers
365 views

Formal proof that every purely reactive agent has behaviorally equivalent standard agent

It kind of makes sense intuitively but I'm not sure about a formal proof. I'll start with briefly listing definitions from Intro to Multiagent systems, Wooldridge, 2002 and then give you my reasoning ...
2 votes
0 answers
98 views

What are the examples of agents that is represent these characteristics?

I'm looking for examples of AI systems or agents that best represent these five characteristics (one example for each characteristics): Reactivity Proactivity Adaptability Sociability Autonomy It ...
8 votes
1 answer
426 views

How would one implement a multi-agent environment with asynchronous action and rewards per agent?

In a single agent environment, the agent takes an action, then observes the next state and reward: ...
  • 183
1 vote
1 answer
294 views

What is the difference between multi-agent and multi-modal systems?

The Wikipedia definitions are as follows Multi-agent systems - A multi-agent system is a computerized system composed of multiple interacting intelligent agents. Multi-modal interaction - Multimodal ...
  • 1,379
4 votes
1 answer
124 views

How to represent players in a multi agent environment so each model can distinguish its own player

So I have 2 models trained with the DQN algorithm that I want to train in a multi-agent environment to see how they react with each other. The models were trained in an environment consisting of 0's ...
  • 41
2 votes
0 answers
98 views

How does Friend-or-Foe Q-learning intuitively work?

I read about Q-Learning and was reading about multi-agent environments. I tried to read the paper Friend-or-Foe Q-learning, but could not understand anything, except for a very vague idea. What does ...
4 votes
0 answers
204 views

Multi Agent Sokoban Search Solvers state of the art

I also asked this question here but I'm repeating it on this SE because I feel it is more relevant. No intention to spam. I am researching into coding a solver for a variant of the Sokoban game with ...
1 vote
0 answers
100 views

What is the best method to deal with heterogeneous multi agent system MAS?

Heterogeneity: Based on the heterogeneity of agents MAS can be divided into two categories namely: homogeneous and heterogeneous. Homogeneous MAS include agents that all have the same characteristics ...
3 votes
1 answer
2k views

How to deal with the terminal state in SARSA in a multi-agent setting?

I'm training a SARSA agent to update a Q function, but I'm confused about how you handle the final state. In this case, when the game ends and there is no $S'$. For example, the agent performed an ...
  • 403
2 votes
1 answer
213 views

Convergence in multi-agent environment

I have a multi-agent environment where agents are trying to optimise the overall energy consumption of their group. Agents can exchange energy between themselves (actions for exchange of energy ...
2 votes
0 answers
80 views

Algorithms for multiple agents problems

Can anyone recommend a reinforcement learning algorithm for a multi-agent environment? In my simplified example, I'm implementing a Q-Learning system with different 10 agents. The agents compete for ...
1 vote
1 answer
156 views

Can Q-learning working in a multi agent environment where every agent learns a behaviour independently?

I am currently exploring multi-agent reinforcement learning. I have multiple agents that communicate with each other and a central service that maintains the environment state. The central service ...
2 votes
1 answer
268 views

Agent collision avoidance java

I am working with a project which is a agent based pedestrian simulation in Java and its is animated with the help of JavaFX. I've tried to read all the social force model papers but my understanding ...
  • 21
2 votes
1 answer
63 views

How to choose evaluation functions for features, when network effects are in place (multi-agent systems)?

So, I have this huge amount of data, which has 7 vector features (float from 0 to 1). I am trying to build a kind of recommendation system, with a twist (it uses agents and negotiations and narratives;...
  • 278
1 vote
3 answers
141 views

To what extent can artificially intelligent agents reliably predict trends in financial markets?

I've gotten curious about this topic and am wondering what the stack exchange community has to say about it. Also, does anyone know of any professors/researchers who have published papers pertaining ...
4 votes
1 answer
151 views

How can I design a hierarchy of agents each of which with different goals?

I read some light material earlier about the possibility of building a hierarchy of agents, where the agents at the leaves solve primitive tasks while higher-level agents are optimized for ...
  • 251
3 votes
1 answer
896 views

Goal oriented Action Planning with multiple Agents

I'm a little bit stuck: I implemented an AI with GOAP (Goal oriented Action Planning, http://alumni.media.mit.edu/~jorkin/gdc2006_orkin_jeff_fear.pdf) for a simulation game. That works fine. Now I ...
  • 116
8 votes
1 answer
35k views

What are some examples of intelligent agents for each intelligent agent class?

There are several classes of intelligent agents, such as: simple reflex agents model-based reflex agents goal-based agents utility-based agents learning agents Each of these agents behaves slightly ...
6 votes
2 answers
177 views

Would a general-purpose AI need to collaborate?

Human beings are more productive in groups than individually, possibly due to the fact that there is a limit to how much one human brain can improve itself in terms of speed of computation and areas ...
5 votes
1 answer
122 views

How can thousand-robot swarm coordinate their moves without bumping into each other?

How can a swarm of small robots (like Kilobots) walking close to each other achieve collaboration without bumping into each other? For example, one study shows programmable self-assembly in a thousand-...
  • 10.3k