Sentence examples for agent decision making from inspiring English sources

Although having smaller intervals facilitates the learning agent decision making, an increase in number of intervals increases the state space size and slows down the learning process convergence rate.

The approach also copes better with explanatory variables of a spatial and local nature (proximate drivers) than policy and socioeconomic factors affecting deforestation agents decision making (ultimate drivers) [19],[25].

The approach also copes better with explanatory variables of a spatial and local nature (proximate drivers) than policy and socioeconomic factors affecting deforestation agents decision making (ultimate drivers) [ 19],[ 25].

This allows an evaluation of policies that accounts for agent decision-making and social and technological change.

We focus on the use of evaluators – configurable, composable modules for data analysis, modeling, and prediction that are chained together at runtime to support agent decision-making.

The LSP method captured different agent decision-making reasoning that is closer to actual human logic which has resulted in the modeling outcomes of urban residential land-use to be in accordance to long term city plans.

A significant benefit of the flexible nature of agent interaction is that the agent decision-making regarding the nature and scope of its interactions can occur at run time.

This paper presents the modulation system of real-time emotional agents (RTEA) and shows how emotional appraisals, that have proven effectively in ethological systems, can influence the agent's decision making.

We discuss implications for the design of embodied agents and decision making systems that use emotion expression to enhance interaction between humans and computers.

To better organize the negotiation knowledge utilized by agents and facilitate agents' adaptive negotiation decision making ability, an ontology-based approach is proposed in this paper.

It provides a framework which allows analysis of stakeholders' (or agents') interactions and decision making.