A large number of computational models of information processing in the basal ganglia have been developed in recent years. Prominent in these are actor-critic models of basal ganglia functioning, which build on the strong resemblance between dopamine neuron activity and the temporal difference prediction error signal in the critic, and between dopamine-dependent long-term synaptic plasticity in...

The acrobot is a two-link robot, actuated only at the joint between the two links. It is one of dicult tasks in reinforcement learning (RL) to control the acrobot because it has nonlinear dynamics and continuous state and action spaces. In this article, we discuss applying the RL to the task of balancing control of the acrobot. Our RL method has an architecture similar to the actor-critic. The ...

Brain-Machine Interfaces (BMIs) can be used to restore function in people living with paralysis. Current BMIs require extensive calibration that increase the set-up times and external inputs for decoder training that may be difficult to produce in paralyzed individuals. Both these factors have presented challenges in transitioning the technology from research environments to activities of daily...

Two-factor theory (Mowrer, 1947, 1951, 1956) remains one of the most influential theories of avoidance, but it is at odds with empirical findings that demonstrate sustained avoidance responding in situations in which the theory predicts that the response should extinguish. This article shows that the well-known actor-critic model seamlessly addresses the problems with two-factor theory, while s...

Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g., when function approximation is involved). Interestingly, there is growing evidence that actor-critic approaches based on phasic dopamine signals play a key role in biological learning through cortical and basal gangli...

A substantial subset of Parkinson's disease (PD) patients suffers from impulse control disorders (ICDs), which are side effects of dopaminergic medication. Dopamine plays a key role in reinforcement learning processes. One class of reinforcement learning models, known as the actor-critic model, suggests that two components are involved in these reinforcement learning processes: a critic, which ...

In real life, learning is greatly speeded-up by the intervention of a teacher who gives examples, or shows, how to perform a certain task. In all this abstract, we let apart structural simpli cations of the problem by the designer which to not deal explicitely with learning. The intervention of the teacher can be realized in di erent ways: verbal explanation, demonstration, guidance, shaping th...

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity ...