Learning logic specifications for policy guidance in pomdps: an inductive logic programming approach
Abstract Partially Observable Markov Decision Processes (POMDPs) are a powerful
framework for planning under uncertainty. They allow to model state uncertainty as a belief …
framework for planning under uncertainty. They allow to model state uncertainty as a belief …
Information-guided planning: an online approach for partially observable problems
MA do Carmo Alves, A Varma… - Advances in …, 2023 - proceedings.neurips.cc
This paper presents IB-POMCP, a novel algorithm for online planning under partial
observability. Our approach enhances the decision-making process by using estimations of …
observability. Our approach enhances the decision-making process by using estimations of …
Decoupled Monte Carlo Tree Search for Cooperative Multi-Agent Planning
The number of agents exponentially increases the complexity of a cooperative multi-agent
planning problem. Decoupled planning is one of the viable approaches to reduce this …
planning problem. Decoupled planning is one of the viable approaches to reduce this …
An Approximate Method for Spatial Task Allocation in Partially Observable Environments
Multi-robot task allocation has many applications in the real world. Robots often have noisy
or local sensor readings, making their workspace partially observable. This paper proposes …
or local sensor readings, making their workspace partially observable. This paper proposes …
Bayesian Model of Communication for Partially Observable Multi-agent Environment
S Adhikari - 2024 - search.proquest.com
We study the communication and interaction among self-interested agents in partially
observable and stochastic domains. This setting has potential applications in several fields …
observable and stochastic domains. This setting has potential applications in several fields …
Information-guided Planning: An Online Approach for Partially Observable Problems
This paper presents IB-POMCP, a novel algorithm for online planning under partial
observability. Our approach enhances the decision-making process by using estimations of …
observability. Our approach enhances the decision-making process by using estimations of …
[PDF][PDF] USING PARTICLE REPRESENTATION OF BELIEFS IN AN ALPHAZERO-BASED REINFORCEMENT LEARNING ALGORITHM FOR PARTIALLY …
H Itoh, Y Kihara, H Fukumoto, H Wakuya - icicel.org
The AlphaZero algorithm is a general reinforcement learning algorithm that defeated world-
champion level programs in chess, shogi, and Go without prior knowledge. However, the …
champion level programs in chess, shogi, and Go without prior knowledge. However, the …