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.

Wage subsidies and hiring chances for the disabled: some causal evidence

We evaluate the effectiveness of wage subsidies as a policy instrument to integrate disabled individuals into the labour market. To identify causal effects, we conduct a large-scale field experiment in Belgium. Our results show that the likelihood of a disabled candidate receiving a positive response to a job application is not positively influenced by revealing entitlement to the Flemish Supporting Subsidy

Continuous low-dose antibiotic prophylaxis to prevent urinary tract infection in adults who perform clean intermittent self-catheterisation: the AnTIC RCT

Peer reviewedPublisher PD

The evolution of representation in simple cognitive networks

Representations are internal models of the environment that can provide guidance to a behaving agent, even in the absence of sensory information. It is not clear how representations are developed and whether or not they are necessary or even essential for intelligent behavior. We argue here that the ability to represent relevant features of the environment is the expected consequence of an adaptive process, give a formal definition of representation based on information theory, and quantify it with a measure R. To measure how R changes over time, we evolve two types of networks---an artificial neural network and a network of hidden Markov gates---to solve a categorization task using a genetic algorithm. We find that the capacity to represent increases during evolutionary adaptation, and that agents form representations of their environment during their lifetime. This ability allows the agents to act on sensorial inputs in the context of their acquired representations and enables complex and context-dependent behavior. We examine which concepts (features of the environment) our networks are representing, how the representations are logically encoded in the networks, and how they form as an agent behaves to solve a task. We conclude that R should be able to quantify the representations within any cognitive system, and should be predictive of an agent's long-term adaptive success.Comment: 36 pages, 10 figures, one Tabl

Equity, Options and Efficiency in the Presence of Moral Hazard

This paper provides a general equilibrium analysis of an economy with production under uncertainty in which the firms' capital (ownership) structure creates a moral hazard problem for their managers. The paper studies the concept of an equilibrium with rational, competitive price perceptions (RCPP) in which investors correctly anticipate the optimal effort of entrepreneurs by observing their financial decisions, and entrepreneurs are aware that investors use their financial decisions as signals. The competitive element in the equilibrium valuation of firms comes from the fact that entrepreneurs cannot affect the market price of risks. It is shown that under appropriate spanning assumptions an RCPP is constrained Pareto optimal. Furthermore, if sufficiently many options are traded, then full optimality can be obtained despite the moral hazard problem: options serve both to increase the span of the market and to provide incentives for entrepreneurs.

Principal-Agent Relationships in Agricultural Cooperatives: An Empirical Analysis from Rural Alberta

Cooperatives throughout North America are consolidating at an increasing rate and for a variety of reasons. While many cooperatives merge with others or are acquired to achieve greater economies of scale, several fail due to changes in the external economy, which make them redundant. Often, such redundancy is reflected in a heightened sense of member dissatisfaction. Many argue that such dissatisfaction is likely to arise in cooperatives as a result of principal-agent problems. In order to determine whether or not cooperative managers maintain the same goals as their owners, this study uses data from a member-survey to compare Alberta cooperative members' objectives with those they believe to be held by their cooperatives' managers. An econometric model of the difference between members' expectations and perceptions shows how various socioeconomic variables affect the extent to which these objectives are aligned. The results of this analysis can help cooperative boards design managerial incentive programs to better align their goals with those of the cooperative membership.Agribusiness,

Theories about architecture and performance of multi-agent systems

Multi-agent systems are promising as models of organization because they are based on the idea that most work in human organizations is done based on intelligence, communication, cooperation, and massive parallel processing. They offer an alternative for system theories of organization, which are rather abstract of nature and do not pay attention to the agent level. In contrast, classical organization theories offer a rather rich source of inspiration for developing multi-agent models because of their focus on the agent level. This paper studies the plausibility of theoretical choices in the construction of multi-agent systems. Multi-agent systems have to be plausible from a philosophical, psychological, and organizational point of view. For each of these points of view, alternative theories exist. Philosophically, the organization can be seen from the viewpoints of realism and constructivism. Psychologically, several agent types can be distinguished. A main problem in the construction of psychologically plausible computer agents is the integration of response function systems with representational systems. Organizationally, we study aspects of the architecture of multi-agent systems, namely topology, system function decomposition, coordination and synchronization of agent processes, and distribution of knowledge and language characteristics among agents. For each of these aspects, several theoretical perspectives exist.