A logic-based calculus of events
New Generation Computing
Combining logic and differential equations for describing real-world systems
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Handbook of theoretical computer science (vol. B)
From theory to practice: the UTEP robot in the AAAI 96 and AAAI 97 robot contests
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
cc-Golog: Towards More Realistic Logic-Based Robot Controllers
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Temporal reasoning in the situation calculus
Temporal reasoning in the situation calculus
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Modeling and querying biomolecular interaction networks
Theoretical Computer Science - Special issue: Computational systems biology
Detecting causal relationships in distributed computations: in search of the holy grail
Distributed Computing
Building knowledge systems in a-prolog
Building knowledge systems in a-prolog
Reasoning and hypothesizing about signaling networks
Reasoning and hypothesizing about signaling networks
Reasoning about continuous processes
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
The Knowledge Engineering Review
Applications of action languages in cognitive robotics
Correct Reasoning
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Modeling molecular interactions in signalling networks is important from various perspectives such as predicting side effects of drugs, explaining unusual cellular behavior and drug and therapy design. Various formal languages have been proposed for representing and reasoning about molecular interactions. The interactions are modeled as triggered events in most of the approaches. The triggering of events is assumed to be immediate: once an interaction is triggered, it should occur immediately. Although working well for engineering systems, this assumption poses a serious problem in modeling biological systems. Our knowledge about biological systems is inherently incomplete, thus molecular interactions are constantly elaborated and refined at different granularity of abstraction. The model of immediate triggers can not consistently deal with this refinement. In this paper we propose an action language to address this problem. We show that the language allows for refinements of biological knowledge, although at a higher cost in terms of complexity.