2 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning
Aditya Kapoor, Sushant Swamy, Kale-ab Tessera +4
In multi-agent environments, agents often struggle to learn optimal policies due to sparse or delayed global rewards, particularly in long-horizon tasks where it is challenging to…
HyperMARL: Adaptive Hypernetworks for Multi-Agent RL
Kale-ab Abebe Tessera, Arrasy Rahman, Amos Storkey +1
Adaptive cooperation in multi-agent reinforcement learning (MARL) requires policies to express homogeneous, specialised, or mixed behaviours, yet achieving this adaptivity remains…
Efficiently Quantifying Individual Agent Importance in Cooperative MARL
Omayma Mahjoub, Ruan de Kock, Siddarth Singh +4
Measuring the contribution of individual agents is challenging in cooperative multi-agent reinforcement learning (MARL). In cooperative MARL, team performance is typically inferred…
How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning
Siddarth Singh, Omayma Mahjoub, Ruan de Kock +4
Establishing sound experimental standards and rigour is important in any growing field of research. Deep Multi-Agent Reinforcement Learning (MARL) is one such nascent field. Althou…