Robotic landing missions like NASA's Mars landers or ISRO's Chandrayaan-3 necessitate reliable guidance and control against uncertain wind, gravity and terrain. Such controllers are not designed by ...

Abstract: This paper reports on learning a reward map for social navigation in dynamic environments where the robot can reason about its path at any time, given agent trajectories and scene geometry.

Reinforcement learning in multi-agent systems explores how multiple decision-making entities can learn to interact optimally within a shared environment. Unlike single-agent settings, where a lone ...

Behavioral analysis of reinforcement schedules examines how the temporal and quantitative arrangement of reinforcers shapes the rate, pattern and persistence of behaviour. Rooted in operant ...