My research interests lie in the field of Artificial Intelligence, more specifically in the Natural Computing and Computational Intelligence fields. My research concentrates on solving Constraint Satisfaction Problems with Evolutionary Algorithms although lately, I started researching the use of Peer-to-Peer Network Architectures in Computational Sociology as part of the NEWTIES project were I am researching the Emergent Behaviour of these networks in a constrained network environment. I am also interested in the field of Interactive Evolutionary Computation, especially were it is used in design and for the evolution of (graphic) art, see for example my EArt page.
The Constraint Satisfaction Problem (CSP) belongs to the constrained problems problem-class. The CSP is a fundamental problem in artificial intelligence and has both practical and theoretical relevance to computer science. Theoretical relevance stems from the fact that the CSP is computationally intractable, in that they are non-deterministic polynomial complete (NP-complete) and can be directly transformed from the Satisfiability Problem (SAT), the original problem proven to be NP. Practical applications include planning, default reasoning, scheduling, etc. Informally, CSPs consist of finding an assignment of values to variables in such a way that a given set of constraints expressed over these variables are satisfied.
Evolutionary algorithms (EAs), sometimes incorrectly referred to as Genetic Algorithms (GAs), are algorithms based on the evolutionary paradigm, first stated by the well known biologist: Charles Darwin.
EAs evolve a population of candidate solutions of a problem, called individuals, guided by the principles of
A Peer-to-Peer Network Architecture (P2P), often simply referred to as peer-to-peer, is a type of computer network in which each workstation or node has equivalent capabilities and responsibilities. This differs from client/server architectures, in which some nodes are dedicated to serving others. A pure peer-to-peer network will not have the notion of clients and servers, but only equal peer nodes that function as both clients and servers to the other nodes on the network. In a peer-to-peer network, any node is able to initiate or complete any supported transaction. Peer nodes may differ in local configuration, processing speed, network bandwidth, and storage quantity. One of the first uses of the phrase peer-to-peer is in 1984, with the development of the Advanced Peer to Peer Networking architecture at IBM. The initialism P2P is often confused to refer to Point-to-Point, as used in telecommunications. More correctly, it should be used to refer to Peer-to-Peer connections.
Computational Sociology is a recently developed branch of sociology that uses computation to analyse social phenomena. The basic premise of computational sociology is to take advantage of computer simulation in the construction of social theories. It involves the understanding of social agents, the interaction among these agents, and the effect of these interactions on the social aggregate. Although the subject matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in contemporal social simulation originated from fields such as physics and artificial intelligence. Computational sociology is often related to the study of social complexity. Social complexity concepts such as complex systems, non-linear interconnection among macro and micro process, and emergence, have entered the computational sociology vocabulary. A practical and well-known example is the construction of a computational model in the form of a artificial society, by which researchers can analyse the structure of a social system.