基本信息
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职业迁徙
个人简介
Research Interests
Our research group focuses on studying and understanding 1) the underlying principles of biological computation, and how these principles can be adopted or modified to extend contemporary computer science methods, and 2) automated causal reasoning, such as abductive inference and Bayesian/belief networks.
Several properties of biologically-inspired computing separate it from more traditional computer science, giving hope that new robust and adaptive software methods can be developed. Examples of this type of computing include neural computation, evolutionary computation, artificial life, self-replicating machines, artificial immune systems, ant colony optimization, L-systems, artificial societies, and swarm intelligence. Our group has worked and/or is working in the following areas:
neural computation
multi-agent artificial life systems
evolutionary computation
cellular automata models of self-replication
We are also focusing on automated causal reasoning using more traditional methods in artificial intelligence. The goal of this research is to model human cognition as a means of generating useful automated reasoning systems. Our group has worked and/or is working in the following areas:
knowledge acquisition
abductive reasoning
Bayesian classification and networks
parsimonious covering theory
We have an active seminar schedule that is open to interested individuals, and a recent undergraduate GEMSTONE research group working on genetic programming and multi-agent systems. Some simple online demonstrations illustrate a simulated self-assembling building , a neural model of cortical spreading depression, a a collection of cellular automata self-replicating structures, that were discovered using genetic programming, and a cellular
研究兴趣
论文共 62 篇作者统计合作学者相似作者
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2023 57th Annual Conference on Information Sciences and Systems (CISS)pp.1-6, (2023)
J. Artif. Intell. Conscious.no. 1 (2020): 95-107
JOURNAL OF SPORT & EXERCISE PSYCHOLOGYno. SUPnan (2017): S134-S135
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openalex(2016)
Neural networks : the official journal of the International Neural Network Societyno. 1 (2015): 208-222
semanticscholar(2014)
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作者统计
#Papers: 62
#Citation: 759
H-Index: 18
G-Index: 25
Sociability: 5
Diversity: 2
Activity: 0
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