Decentralized POMDPs

Decentralized POMDPs - Frans A. Oliehoek

1: Execution of a decentralized POMDP. a reward depending on the state and the actions of both agents. Finally, each agent receives an individual observation of ...

Decentralized partially observable Markov decision process

The decentralized partially observable Markov decision process (Dec-POMDP) is a model for coordination and decision-making among multiple agents.

Decentralized Control of Partially Observable Markov Decision ...

Hence, solving decen- tralized multiagent optimal control problems represented as. Dec-POMDPs generally involves approximation techniques and identifying ...

Decentralized POMDPs - SpringerLink

This chapter presents an overview of the decentralized POMDP (Dec- POMDP) framework. In a Dec-POMDP, a team of agents collaborates to maximize a global ...

Planning with Macro-Actions in Decentralized POMDPs

Decentralized partially observable Markov decision processes. (Dec-POMDPs) are general models for decentralized deci- sion making under uncertainty. However, ...

A Concise Introduction to Decentralized POMDPs

controllers for POMDPs and decentralized POMDPs. Journal of Autonomous. Agents and Multi-Agent Systems, 21(3):293–320, 2010. 117. Page 125. 118.

Modeling and Planning with Macro-Actions in Decentralized POMDPs

Decentralized partially observable Markov decision processes (Dec-POMDPs) are general models for decentralized multi-agent decision making under uncertainty ...

Taming Decentralized POMDPs - University of Southern California

Given a group of agents, the problem of deriving sep- arate policies for them that maximize some joint reward can be modeled as a decentralized POMDP (Partially ...

A Concise Introduction to Decentralized POMDPs: | Guide books

Sections ... This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs) ...

Bounded Policy Iteration for Decentralized POMDPs - IJCAI

We present a bounded policy iteration algorithm for infinite-horizon decentralized POMDPs. Policies are represented as joint stochastic finite-state con-.

Optimally Solving Two-Agent Decentralized POMDPs Under One ...

Optimally solving decentralized partially observ- able Markov decision processes (Dec-POMDPs) under either full or no information sharing re-.

Decentralized Learning of Finite-Memory Policies in Dec-POMDPs

In this paper, we study MARL in decentralized partially observable Markov decision processes (Dec-POMDPs) with partial history sharing.

A Concise Introduction to Decentralized POMDPs - ResearchGate

decentralized POMDP (Dec-POMDP). ... cooperative agents that are situated in a stochastic, partially observable environment. ... D={1,...,n}is the set of nagents. • ...

A Concise Introduction to Decentralized POMDPs - SpringerLink

About this book. This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec- ...

Open Decentralized POMDPs | IEEE Conference Publication

This paper introduces a new model, called the Open Dec-POMDP, allowing us to consider agents that can enter and leave the system during the execution of the ...

Sample Bounded Distributed Reinforcement Learning for ...

Decentralized partially observable Markov decision pro- cesses (Dec-POMDPs) offer a powerful modeling technique for realistic multi-agent coordination problems ...

View of Optimal and Approximate Q-value Functions for ...

09/07; published 05/08Optimal and Approximate Q-value Functionsfor Decentralized POMDPsFrans A. [email protected] Systems Lab Amsterdam ...

A Concise Introduction to Decentralized POMDPs - Semantic Scholar

This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs).

Sufficient Plan-Time Statistics for Decentralized POMDPs - IJCAI

Optimal decentralized decision making in a team of cooperative agents as formalized by decentralized. POMDPs is a notoriously hard problem. A major obstacle is ...

Optimally Solving Two-Agent Decentralized POMDPs Under One ...

Abstract. Optimally solving decentralized partially observable Markov decision processes under either full or no information sharing received significant ...