Deception in Social Learning: A Multi-Agent Reinforcement Learning Perspective

06/09/2021
by   Paul Chelarescu, et al.
0

Within the framework of Multi-Agent Reinforcement Learning, Social Learning is a new class of algorithms that enables agents to reshape the reward function of other agents with the goal of promoting cooperation and achieving higher global rewards in mixed-motive games. However, this new modification allows agents unprecedented access to each other's learning process, which can drastically increase the risk of manipulation when an agent does not realize it is being deceived into adopting policies which are not actually in its own best interest. This research review introduces the problem statement, defines key concepts, critically evaluates existing evidence and addresses open problems that should be addressed in future research.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/23/2019

The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition

Learning in multi-agent scenarios is a fruitful research direction, but ...
research
09/04/2022

Learning to Deceive in Multi-Agent Hidden Role Games

Deception is prevalent in human social settings. However, studies into t...
research
04/24/2023

Stubborn: An Environment for Evaluating Stubbornness between Agents with Aligned Incentives

Recent research in multi-agent reinforcement learning (MARL) has shown s...
research
09/26/2018

Learning through Probing: a decentralized reinforcement learning architecture for social dilemmas

Multi-agent reinforcement learning has received significant interest in ...
research
06/10/2021

ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations

Multi-agent simulations provide a scalable environment for learning poli...
research
11/02/2020

Interpreting Graph Drawing with Multi-Agent Reinforcement Learning

Applying machine learning techniques to graph drawing has become an emer...
research
07/29/2023

PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas

Recent research has demonstrated the potential of reinforcement learning...

Please sign up or login with your details

Forgot password? Click here to reset