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Adam Callaghan

2 papers hereh-index 27 citations3 works total

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author position
  • first author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • cs.NE1

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.LGShow all

1 paper · 1 filter

cs.LG2025

MOMA-AC: A preference-driven actor-critic framework for continuous multi-objective multi-agent reinforcement learning

Adam Callaghan, Karl Mason, Patrick Mannion

This paper addresses a critical gap in Multi-Objective Multi-Agent Reinforcement Learning (MOMARL) by introducing the first dedicated inner-loop actor-critic framework for continuo…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.