It has been discovered about a decade ago that autistic people cannot properly understand and reproduce mental states and emotions. In this study we suggest a particular emotion rehabilitation strategy, based on playing with mental simulator that is capable of modeling the mental and emotional states. We present the model of mental world, approach the formalization of emotions, describe interfa...

We analyze the results of assistance to individuals with autism in reasoning about mental world. This assistance is provided by a natural language multiagent simulator of mental states, NL_MAMS (Galitsky 2013b). It assists in the tasks which are the hardest for autistic reasoning: operating with mental states and actions. Autistic patients are trained to perform a number of reasoning exercises....

This paper describes APE (the Atlas Planning Engine), the reactive planner at the center of the Atlas dialogue management system. The goal of Atlas is to build conversation-based systems, where turns in the “conversation” may include graphical actions and/or text. Since APE can be used to generate a dialogue involving arbitrarily nested discourse constructs, it is more powerful than dialogue pl...

In realistic multiagent systems, learning on the basis of complete state information is not feasible. We introduce adaptive state focus Q-learning, a class of methods derived from Q-learning that start learning with only the state information that is strictly necessary for a single agent to perform the task, and that monitor the convergence of learning. If lack of convergence is detected, the l...

We use a version of Statecharts to represent multiagent plans and transactions. Although epistemic and deontic logic are abstract and appropriate for specification, we argue that an agent must know that abstract modal properties apply to it and its collaborators. We develop a language that describes Statechart features but also expresses knowledge, common knowledge, and obligations. The hierarc...

The application of argumentation theories and techniques in multi-agent systems has become a prolific area of research. Argumentation allows agents to harmonize two types of disagreement situations: internal, when the acquisition of new information (e.g. about the environment or about other agents) produces incoherences in the agents’ mental state; and external, when agents that have different ...

The study analyzed factors that motivate agricultural extension agents in Agricultural Development Programme of Abia State. Primary data were collected from 96 extension agents in Abia State, Nigeria who were selected using multi-stage random sampling technique. Data were analyzed using descriptive statistics, mean score, ordered logit and Spearman rank correlation. It was revealed that 58.3% o...

Component-level predictive maintenance schedules are developed to maximize multi-state system lifetime, considering degrading component multi-state behavior. To maximize the system time-to-replacement, the predictive maintenance schedule is based on individual component performance degradation trends, system performance requirements and component maintenance thresholds. This work is an extensio...

Reliability analysis is one of the important constituent parts of elevator safety evaluation. In order to obtain the exact value of fault probability of components in elevator system, by combining fuzzy theory with Bayesian network approach, we proposed a reliability analysis method of multi-state system based on fuzzy Bayesian networks. By expanding the traditional two-state Bayesian network t...

This paper deals with robust synchronization of directed and undirected multi-agent networks with uncertain agent dynamics. Given a networkwith identical nominal dynamics, we allow uncertainty in the form of coprime factor perturbations of the transfer matrix of the agent dynamics. These perturbations are assumed to be stable and have H∞-norm that is bounded by an a priori given desired toleran...