DeepAI AI Chat
Log In Sign Up

Attention Actor-Critic algorithm for Multi-Agent Constrained Co-operative Reinforcement Learning

01/07/2021
by   P. Parnika, et al.
0

In this work, we consider the problem of computing optimal actions for Reinforcement Learning (RL) agents in a co-operative setting, where the objective is to optimize a common goal. However, in many real-life applications, in addition to optimizing the goal, the agents are required to satisfy certain constraints specified on their actions. Under this setting, the objective of the agents is to not only learn the actions that optimize the common objective but also meet the specified constraints. In recent times, the Actor-Critic algorithm with an attention mechanism has been successfully applied to obtain optimal actions for RL agents in multi-agent environments. In this work, we extend this algorithm to the constrained multi-agent RL setting. The idea here is that optimizing the common goal and satisfying the constraints may require different modes of attention. By incorporating different attention modes, the agents can select useful information required for optimizing the objective and satisfying the constraints separately, thereby yielding better actions. Through experiments on benchmark multi-agent environments, we show the effectiveness of our proposed algorithm.

READ FULL TEXT
05/08/2019

Actor-Critic Algorithms for Constrained Multi-agent Reinforcement Learning

In cooperative stochastic games multiple agents work towards learning jo...
12/14/2019

Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator

Multi-agent reinforcement learning has been successfully applied to a nu...
12/23/2019

Discrete and Continuous Action Representation for Practical RL in Video Games

While most current research in Reinforcement Learning (RL) focuses on im...
12/17/2022

Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning

This paper presents a novel federated reinforcement learning (Fed-RL) me...
11/16/2017

Systems, Actors and Agents: Operation in a multicomponent environment

Multi-agent approach has become popular in computer science and technolo...
05/17/2019

A Regularized Opponent Model with Maximum Entropy Objective

In a single-agent setting, reinforcement learning (RL) tasks can be cast...

Code Repositories