Cognitive AI Systems
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learn-to-follow
learn-to-follow Public[AAAI-2024] Follower: This study addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed Follower approach utilizes a combination of a planning algorithm f…
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when-to-switch
when-to-switch Public"When to Switch" Implementation: Addressing the PO-MAPF challenge with RePlan & EPOM policies. This repo includes search-based re-planning, reinforcement learning techniques, and three mixed polici…
Repositories
- MAPF-GPT Public
This repository contains MAPF-GPT, a deep learning-based model for solving MAPF problems. Trained with imitation learning on trajectories produced by LaCAM, it generates actions under partial observability without heuristics or agent communication. MAPF-GPT excels on unseen instances and outperforms state-of-the-art solvers.
Cognitive-AI-Systems/MAPF-GPT’s past year of commit activity - pogema-benchmark Public
This is an umbrella repository that contains links and information about all the tools and algorithms related to the POGEMA Benchmark.
Cognitive-AI-Systems/pogema-benchmark’s past year of commit activity - pogema Public
POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.
Cognitive-AI-Systems/pogema’s past year of commit activity - him-agent Public
The Hierarchical Intrinsically Motivated Agent (HIMA) is an algorithm that is intended to exhibit an adaptive goal-directed behavior using neurophysiological models of the neocortex, basal ganglia, and thalamus.
Cognitive-AI-Systems/him-agent’s past year of commit activity - pogema-toolbox Public
Cognitive-AI-Systems/pogema-toolbox’s past year of commit activity - IGOR Public
Cognitive-AI-Systems/IGOR’s past year of commit activity - RATE Public
Cognitive-AI-Systems/RATE’s past year of commit activity - TransPath Public
This repository contains a deep learning-based approach for improving A* search efficiency on grid graphs. By learning instance-dependent heuristic proxies like correction factors and path probability, our method significantly reduces computational effort in obstacle-rich environments.
Cognitive-AI-Systems/TransPath’s past year of commit activity - mats-lp Public
[AAAI-2024] MATS-LP addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed approach utilizes a combination of Monte Carlo Tree Search and reinforcement learning for resolving conflicts.
Cognitive-AI-Systems/mats-lp’s past year of commit activity - when-to-switch Public
"When to Switch" Implementation: Addressing the PO-MAPF challenge with RePlan & EPOM policies. This repo includes search-based re-planning, reinforcement learning techniques, and three mixed policies for pathfinding in partially observable multi-agent environments. 🤖🛤️
Cognitive-AI-Systems/when-to-switch’s past year of commit activity
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