Two papers accepted at ICCM

Congratualtions to us for another successful set of submissions to the International Conference on Cognitive Modeling. The first one will be presented as a talk, and the second as a poster. The conference is in Amsterdam in July.

Improving Reinforcement Learning with Biologically Motivated Continuous State Representations
- M Bartlett, K Simone, N Dumont, M Furlong, C Eliasmith, J Orchard, TC Stewart
“In this paper we show that biologically motivated representations of continuous spaces form a valuable state representation for RL. We use models of grid and place cells in the Medial Entorhinal Cortex (MEC) and hippocampus, respectively, to represent continuous states in a navigation task and in the CartPole control task. … We demonstrate our approach provides significantly increased robustness”

Novelty Detection, Insect Olfaction, Mismatch Negativity, and the Representation of Probability in the Brain
- TC Stewart, M Furlong, K Simone, M Bartlett, J Orchard
“We present a unified model of how groups of neurons can represent and learn probability distributions using a biologically plausible online learning rule. We first present this in the context of insect olfaction, where we map our model onto a well-known biological circuit where a single output neuron represents whether the current stimulus is novel or not. We show that the model approximates a Bayesian inference process, providing an explanation as to why the current flowing into the output neuron is proportional to the expected probability of that stimulus. Finally, we extend this model to show that the same circuit can detect temporal patterns such as those violations of expectations that produce the EEG mismatch negativity signal.”