Sentence examples for reinforcement policy from inspiring English sources

Objectives – The authors wanted to assess the impact of an "isolation" reinforcement policy in a French general hospital intensive care unit (ICU), between 1994 and 1999.

Using these techniques requires a deviation from the Partially Observable Markov Decision Processes (POMDP) and some innovations: heuristic techniques for generalizing the experience and for treating the partial observability; a technique for the speed adjournment of the Q function; the definition of a special reinforcement policy adequate for learning a complex task without supervision.

Within this large picture, the long-term review of different cases may provide useful discussions for the guidance and reinforcement of policy assessment.

The paper is organized as follows: first, we describe the syntactic language games, in particular the type of grammar and syntactic rules of the robots team's language and the dynamic process of the language games which are based on dialogic communicative acts and a reinforcement learning policy that allows the robot team to converge to a common language.

Policy coherence (synergy and mutual reinforcement between policies) was said to have decreased over the same period.

Arab countries worried that the administration was backing off its previous insistence on a complete freeze, but Mrs. Clinton denied that, saying that she was offering "positive reinforcement" for policies that headed in that direction.

Moreover, there must be societal support, training reinforcement, corporate policies, and laws to ensure that those who report illicit activities are protected.

Constant reinforcement of the policy and its active promotion were regarded as central determinants of successful policies.

It finds that while presenting the carbon footprint information is generally viewed positively by consumers, managerial and policy reinforcement is necessary for it to become a determinant of consumer choice.

However, the reinforcement of the policies that address health insurance for vulnerable groups will depend on the mandatory status of these policies and the capacity of local governments to implement them.

The output synchronization problem is then formulated as an optimal control problem and a novel model-free off-policy reinforcement learning algorithm is developed to solve the optimal output synchronization problem online in real time.