Results 31 to 40 of about 11,728 (310)

A Gradient-Based Reinforcement Learning Algorithm for Multiple Cooperative Agents

IEEE Access, 2018
Multi-agent reinforcement learning (MARL) can be used to design intelligent agents for solving cooperative tasks. Within the MARL category, this paper proposes the probability of maximal reward based on the infinitesimal gradient ascent (PMR-IGA ...
Zhen Zhang, Dongqing Wang, Dongbin Zhao, Qiaoni Han, Tingting Song   +4 more
doaj   +1 more source

On a Simplified Method of Defining Characteristic Function in Stochastic Games

Mathematics, 2020
In the paper, we propose a new method of constructing cooperative stochastic game in the form of characteristic function when initially non-cooperative stochastic game is given. The set of states and the set of actions for any player is finite.
Elena Parilina, Leon Petrosyan
doaj   +1 more source

n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications

Sensors, 2022
This paper provides a conceptual foundation for stochastic duels and contains a further study of the game models based on the theory of stochastic duels.
Manik Gupta, Bhisham Sharma, Akarsh Tripathi, Shashank Singh, Abhishek Bhola, Rajani Singh, Ashutosh Dhar Dwivedi   +6 more
doaj   +1 more source

Tutoring and Multi-Agent Systems: Modeling from Experiences

Informatics in Education, 2010
Tutoring systems become complex and are offering varieties of pedagogical software as course modules, exercises, simulators, systems online or offline, for single user or multi-user.
Abdellah BENNANE
doaj   +1 more source

Reactive Strategies: An Inch of Memory, a Mile of Equilibria

Games, 2021
We explore how an incremental change in complexity of strategies (“an inch of memory”) in repeated interactions influences the sets of Nash equilibrium (NE) strategy and payoff profiles. For this, we introduce the two most basic setups of repeated games,
Artem Baklanov
doaj   +1 more source

Recursive Concurrent Stochastic Games

, 2006
. We study Recursive Concurrent Stochastic Games (RCSGs), extending our recent analysis of recursive simple stochastic games [14, 15] to a concurrent setting where the two players choose moves simultaneously and independently at each state.
Mihalis Yannakakis, Yannakakis, Mihalis, Etessami, Kousha; id_orcid, Kousha Etessami   +3 more
core   +1 more source

Cooperation between Emotional Players

Games, 2020
This paper uses the framework of stochastic games to propose a model of emotions in repeated interactions. An emotional player can be in either a friendly, a neutral, or a hostile state of mind.
Lina Andersson
doaj   +1 more source

Deterministic Markov Nash equilibria for potential discrete-time stochastic games [PDF]

, 2022
summary:In this paper, we study the problem of finding deterministic (also known as feedback or closed-loop) Markov Nash equilibria for a class of discrete-time stochastic games.
Fonseca-Morales, Alejandra
core   +1 more source

Variational Stochastic Games

Proceedings of the 2024 Sixth International Conference on Distributed Artificial Intelligences
The Control as Inference (CAI) framework has successfully transformed single-agent reinforcement learning (RL) by reframing control tasks as probabilistic inference problems. However, the extension of CAI to multi-agent, general-sum stochastic games (SGs) remains underexplored, particularly in decentralized settings where agents operate independently ...
Zhiyu Zhao, Haifeng Zhang
openaire   +2 more sources

Correlated Equilibrium in Stochastic Games [PDF]

Games and Economic Behavior, 2002
In this paper the existence of correlated equilibrium payoffs in \(n\)-player stochastic games is studied. A correlation device chooses for every player a private signal before the start of play and sends to each player the signal chosen for him. Then each player can base his choice of an action on the private signal that he has received.
Eilon Solan, Nicolas Vieille
openaire   +5 more sources