Empirically supported psychological treatments:The challenges of comorbid psychiatric and behavioral disorders in people with intellectual disability

This paper reviews the current state of knowledge on psychological interventions with empirical evidence of efficacy in treating common psychiatric and behavioral disorders in people with intellectual disability(ID)at all stages of their life.We begin with a brief presentation of what is meant by psychiatric and behavioral disorders in this population,along with an explanation of some of the factors that contribute to the increased psychosocial vulnerability of this group to present with these problems.We then conduct a review of empirically supported psychological therapies used to treat psychiatric and behavioral disorders in people with ID.The review is structured around the three generations of therapies:Applied behavior analysis(e.g.,positive behavior support),cognitive behavioral therapies(e.g.,mindfulness-based cognitive therapy),and contextual therapies(e.g.,dialectical behavior therapy).We conclude with some recommendations for professional practice in the fields of ID and psychiatry.

Forecasting macro parameters representing the behavior of an applied multi-agent system

Under consideration is the method of probabilistic forecasting of macro parameters representing general patterns of an applied multi-agent system behavior.This system introduces the game interaction between a set of agents and a target.The behavior dynamics of such a system is described by a discrete-state discrete-time Markov random process and represented in the terms,which are considered convenient for interpretation and practical control of macro parameters.The corresponding calculations are based on common characteristics of the initial conditions.The probabilistic model of behavior of the system is generalized for the case of the mobile target and supplemented with formulas for the dynamical calculation of probabilistic distributions of the target’s defeat by the agents as well as the agent’s defeat by the target.

An applied multi-agent system within the framework of a player-centered probabilistic computer game

The probabilistic model to represent the behavior of an applied multi-agent system that introduces the interaction between a set of agents and Player has been developed within the framework of player-centered probabilistic computer games.The approach features are given with the aid of a game developed for testing cognitive abilities.The agent’s behavior is nondeterministic and therefore unpredictable from Player viewpoint.The system allows both coordinated and autonomous agent’s behavior that depends on availability of information about the presence and position of workable agents for each other.Agent’s behavior is determined with the aid of the algorithm that includes identification of the probabilistic model parameters using maximized objective functions representing individual and group probabilities for Player defeating.Both the model and algorithm ensure the behavior control for relevant applied multi-agent systems.