4 papers
A Novel Framework for Uncertainty-Driven Adaptive Exploration
Leonidas Bakopoulos, Georgios Chalkiadakis
Adaptive exploration methods propose ways to learn complex policies via alternating between exploration and exploitation. An important question for such methods is to determine the…
Graph Neural Networks, Deep Reinforcement Learning and Probabilistic Topic Modeling for Strategic Multiagent Settings
Georgios Chalkiadakis, Charilaos Akasiadis, Gerasimos Koresis +2
This paper provides a comprehensive review of mainly GNN, DRL, and PTM methods with a focus on their potential incorporation in strategic multiagent settings. We draw interest in (…
On Altruism and Spite in Bimatrix Games
Michail Fasoulakis, Leonidas Bakopoulos, Charilaos Akasiadis +1
One common assumption in game theory is that any player optimizes a utility function that takes into account only its own payoff. However, it has long been observed that in real li…
Seldonian Reinforcement Learning for Ad Hoc Teamwork
Edoardo Zorzi, Alberto Castellini, Leonidas Bakopoulos +2
Most offline RL algorithms return optimal policies but do not provide statistical guarantees on desirable behaviors. This could generate reliability issues in safety-critical appli…