Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
Randomized neural networks are immortalized in this well-known AI Koan: In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What a...
A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically r...
Abstract—This paper considers maximizing throughput utility in a multi-user network with partially observable Markov ON/OFF channels. Instantaneous channel states are never known...
We present a novel stochastic, adaptive strategy for tracking multiple people in a large network of video cameras. Similarities between features (appearance and biometrics) observ...