A multi-agent system with application in project scheduling

The new economic and social dynamics increase project complexity and makes scheduling problems more difficult, therefore scheduling requires more versatile solutions as Multi Agent Systems (MAS). In this paper the authors analyze the implementation of a Multi-Agent System (MAS) considering two scheduling problems: TCPSP (Time-Constrained Project Scheduling), and RCPSP (Resource-Constrained Project Scheduling). The authors propose an improved BDI (Beliefs, Desires, and Intentions) model and present the first the MAS implementation results in JADE platform.multi-agent architecture, scheduling, project management, BDI architecture, JADE.

Epistemic virtues, metavirtues, and computational complexity

I argue that considerations about computational complexity show that all finite agents need characteristics like those that have been called epistemic virtues. The necessity of these virtues follows in part from the nonexistence of shortcuts, or efficient ways of finding shortcuts, to cognitively expensive routines. It follows that agents must possess the capacities – metavirtues –of developing in advance the cognitive virtues they will need when time and memory are at a premium

A Calculus of Bounded Capacities

Resource control has attracted increasing interest in foundational research on distributed systems. This paper focuses on space control and develops an analysis of space usage in the context of an ambient-like calculus with bounded capacities and weighed processes, where migration and activation require space. A type system complements the dynamics of the calculus by providing static guarantees that the intended capacity bounds are preserved throughout the computation

Behavioral Aspects of Organizational Learning and Adaptation

In this paper, I seek to understand the behavioral basis of higher organizational learning and adaption as a teleological dynamic equilibrium process to decipher the underlying psycho-physiological aspects of individual cognitive learning related to organizational adaption. Dynamics of cognitive learning has some differential paths within the neural circuitry which follows certain patterns that leads to individual as well as organized evolution in course of a learning process. I undertake a comparative analysis of human cognitive and behavioral changes and the active mechanisms underlying animal behavior and learning processes to understand the differential patterns of these adaptive changes in these two species. Cognitive behavioral learning processes have certain economic perspectives which help an individual to attain efficiency in workplace adaptation and in learning which however, the individual when being part of an alliance, ember positive influence on the society or organization as a whole. Comparatively, in primates, I review some empirical evidences drawn from chronological studies about cognitive behavioral learning process and adaptation as well as the presence of the capacity of making attributions about mental states, which exists in rudimentary form in chimpanzees and apes. Following this, I apply the outcomes of the findings on different aspects of human cognitive and adaptive behavioral learning-induced evolutionary changes and how human beings are able to exploit the presence of these additive advantages under cluster settings.Animal behavior, cognitive economics, motivational energy, neural adaptation, neuroscience, Organizational learning, organizational adaptation, teleological process

Herbert Simon's decision-making approach: Investigation of cognitive processes in experts

This is a post print version of the article. The official published can be obtained from the links below - PsycINFO Database Record (c) 2010 APA, all rights reserved.Herbert Simon's research endeavor aimed to understand the processes that participate in human decision making. However, despite his effort to investigate this question, his work did not have the impact in the “decision making” community that it had in other fields. His rejection of the assumption of perfect rationality, made in mainstream economics, led him to develop the concept of bounded rationality. Simon's approach also emphasized the limitations of the cognitive system, the change of processes due to expertise, and the direct empirical study of cognitive processes involved in decision making. In this article, we argue that his subsequent research program in problem solving and expertise offered critical tools for studying decision-making processes that took into account his original notion of bounded rationality. Unfortunately, these tools were ignored by the main research paradigms in decision making, such as Tversky and Kahneman's biased rationality approach (also known as the heuristics and biases approach) and the ecological approach advanced by Gigerenzer and others. We make a proposal of how to integrate Simon's approach with the main current approaches to decision making. We argue that this would lead to better models of decision making that are more generalizable, have higher ecological validity, include specification of cognitive processes, and provide a better understanding of the interaction between the characteristics of the cognitive system and the contingencies of the environment

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2