Case-Based Reasoning (CBR) is a methodology that reuses the solutions of previous similar problems to solve new problems. Adaptation is the most difficult stage in the CBR cycle, especially, when the solution space is multi-dimensional. This paper discusses the adaptation of a high dimensional solution space and proposes a possible approach to it. A Visualisation induced Self Organising Map (Vi...

Public-private service networks (PPSN) consist of social and technology components. Development of PPSN is ill-understood as these are dependent on a complex mix of interactions among stakeholders and their technologies and is influenced by contemporary developments. The aim of this paper is to advance our understanding of PPSN by modeling its evolution. Agent-based modeling (ABM) is used to un...

In a multiagent system, coalition formation is a coordination method for agents aiming to form groups of interest. In this paper, we focus on the particular context where agents are self-interested and plan their activities. We develop a new coalition formation model that uses the plans of the agents to guide the search for the coalitions and analyzes the coalition proposals already suggested b...

A software component must be tested every time it is reused, to guarantee the quality of both the component itself and the system in which it is to be integrated. To reduce testing costs, we propose a model to build highly testable components by embedding testing and monitoring mechanisms inside them. The approach is useful to component developers, who can use these built-in test capabilities i...

The explanation of the results is a key point of automatic problem solvers. CBR systems solve a new problem by assessing its similarity with already solved cases and they commonly show the user the set of cases that have been assessed as the most similar to the new problem. Using the notion of symbolic similarity, our proposal is to show the user a symbolic description that makes explicit what ...

This study extends previous research that showed how informal social sanctions can backfire when members prefer friendship over enforcement of group norms. We use a type of neural network to model the coordination of informal social control in a small group of adaptive agents confronted with a social dilemma. This model incorporates two mechanisms of social influence, informal sanctions and imi...

Cells of the immune system must search among billions of healthy cells in order to find and neutralize a small number of infected cells before pathogens replicate to sufficient numbers to cause disease or death. The immune system uses information signals to accomplish this search quickly. Here we use a computationally tractable and scalable differential equation model and a spatially explicit a...

Inspired by the chemotaxis interaction of living cells, we have developed an agent-based approach for self-organizing shape formation. Since all our simulations begin with a different uniform random configuration and our agents move stochastically, it has been observed that the self-organization process may form two or more stable final configurations. These differing configurations may be char...

Location-based applications and services become increasingly important for mobile users. They take into account a mobile user's current location and provide a location-dependent output. To support developers of location-based services, the Nimbus framework hides specific details of positioning systems and provides uniform output containing physical as well as symbolic location information, whic...

Multi-sided platforms are increasingly common, which is no surprise given the winner-take-all dynamics in platform-based markets. That is, the platform with the biggest installed base of buyers and sellers can arguably sustain its competitive advantage because of positive indirect network effects. We reexamine this argument with an agent-based simulation model, where we allow for variety seekin...