Authors:
Veronica Dahl
1
;
Pedro Barahona
2
;
Gemma Bel-Enguix
3
and
Ludwig Krippahl
2
Affiliations:
1
Rovira i Virgili University;Simon Fraser University, Canada
;
2
Universidade Nova de Lisboa, Portugal
;
3
Rovira I Virgili University, Spain
Keyword(s):
Biology, Cognitive sciences, Concept formation, Multi-agent systems, Molecular biology, Nucleic acid string
analysis, Lung cancer detection, Logic programming, Constraint handling rules, Logic grammars, Constraint
handling rule grammars, Language processing, RNA design.
Abstract:
Constraint based models that are useful for processing biological information have been successfully put forward recently, e.g. for representing multi-disciplinary biological knowledge in view of cancer diagnosis, and for reconstructing RNA sequences from secondary structure. Here we generalize such results into a model for biological concept formation which can interact with heterogeneous agents through constraint-based reasoning. Our model includes linguistic agents, probabilistic agents for mining nucleic acid, and illness diagnosis agents. Information is selected automatically as a side effect of (the system) searching through applicable CHR rules, and automatically transformed when a rule triggers; decisions follow from the normal operation of the rules, and cognitive structure is given by properties that the concepts a given rule is trying to relate must satisfy. Moreover the user can declare under what circumstances a given property or properties can be relaxed. Concepts fo
rmed under relaxed properties result in output which signals not only what concepts were formed, but which of the properties associated with the construction of those concepts were satisfied and which were not. This allows us human-like flexibility while maintaining direct executability.
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