Neurophilosophy: toward a unified science of the mind-brain
Neurophilosophy: toward a unified science of the mind-brain
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Cognitive and social simulation of criminal behaviour: the intermittent explosive disorder case
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Case analysis of criminal behaviour
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
The development of Urban Crime Simulator
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application
Reactive reasoning and planning
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
On the use of reduction relations to relate different types of agent models
Web Intelligence and Agent Systems
Analyzing police patrol routes by simulating the physical reorganization of agents
MABS'05 Proceedings of the 6th international conference on Multi-Agent-Based Simulation
Collective representational content for shared extended mind
Cognitive Systems Research
| Hi-index | 0.00 |
This article discusses how a cognitive modelling approach for criminal behaviour can be related to a biological modelling approach. The discussion is illustrated by a case study for the behaviour of three types of violent criminals as known from literature within the area of Criminology. A cognitive model is discussed that can show each of the behaviours of these types of criminals, depending on the characteristics set and inputs in terms of stimuli from the environment. Based on literature in Criminology about motivations and opportunities and their underlying biological factors, it is shown by a formal interpretation mapping how the model can be related to a biological grounding. This formal mapping covers ontology elements for states and dynamic properties for processes, and thus shows how the cognitive model can be biologically grounded.