3 papers
cs.MA2026
Moral Hazard in Multi-Agent Language Models
Dane Malenfant
Cooperation can fail when socially valuable effort is costly, hard to observe, and benefits mainly someone else. Building on Holmstrom's model of moral hazard in teams, the Dialogu…
cs.AI2026
Reinforcing the World's Edge: A Continual Learning Problem in the Multi-Agent-World Boundary
Dane Malenfant
In a stationary decentralized Markov game, learning peers generate an episode-indexed sequence of induced MDPs for any focal agent. The joint game remains stationary while the foca…
cs.LG2025
The challenge of hidden gifts in multi-agent reinforcement learning
Dane Malenfant, Blake A. Richards
Sometimes we benefit from actions that others have taken even when we are unaware that they took those actions. For example, if your neighbor chooses not to take a parking spot in…