Predicting reward is essential in learning approach behaviors. Dopaminergic activity has been implicated in reward, movement, and cognitive processes, all essential elements in learning. The nucleus accumbens (NAc) receives converging inputs from corticolimbic information-processing areas and from mesolimbic dopamine neurons originating in the ventral tegmental area. Previously, we reported tha...

Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP). Unlike the case of an MDP, the notion of an optimal policy for a BMDP is not entirely straightforward. We consider two notions of optimality based on optimistic and pessimistic criteria. These have been analyzed for discounted BMDPs. Here we pro...

As the same framework of Fuzzy decision processes with the discounted case we will specify an average fuzzy criterion model and develop its optimization by “fuzzy max order” under appropriate conditions. The average reward is characterized, by introducing a relative value function, as a unique solution of the associated equation. Also we derive the optimality equation using the “vanishing disco...

The specification of a Markov decision process (MDP) can be difficult. Reward function specification is especially problematic; in practice, it is often cognitively complex and time-consuming for users to precisely specify rewards. This work casts the problem of specifying rewards as one of preference elicitation and aims to minimize the degree of precision with which a reward function must be ...

Animal findings have highlighted the modulatory role of phasic dopamine (DA) signaling in incentive learning, particularly in the acquisition of reward-related behavior. In humans, these processes remain largely unknown. In a recent study, we demonstrated that a single low dose of a D2/D3 agonist (pramipexole)-assumed to activate DA autoreceptors and thus reduce phasic DA bursts-impaired reward...

We test the hypothesis that motivational and cognitive processes are linked by a specific neural system to reach maximal efficiency. We studied six normal subjects performing a working memory paradigm (n-back tasks) associated with different levels of monetary reward during an fMRI session. The study showed specific brain activation in relation with changes in both the cognitive loading and the...

Temperamental-traits (e.g. threat/reward-sensitivity) are found to modulate cognitive-control and attentional-processes. Yet, it is unclear exactly how these traits interact with emotional-stimuli in the modulation of cognitive-control, as reflected by the N2 event-related potential (ERP), and attentional-processes, as reflected by the P2 and P3 ERPs. Here in an ERP emotional-Go/NoGo task, 36 p...

We investigate the computability of problems in probabilistic planning and partially observable infinite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic finite automata is adapted to show that the following problem of plan existence in probabilistic planning is undecidable: given a probabilistic planning problem, determine whether there ex...

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of preand postsynaptic neural activity. These data are inconsistent with common mod...

We investigate the computability of problems in probabilistic planning and partially observable innnite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic nite automata is adapted to show that the following problem of plan existence in probabilistic planning is undecidable: given a probabilistic planning problem, determine whether there exist...