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Efficient Forward Chaining for Declarative Rules in a Multi-Agent Modelling Language

Contents


Contents
Abstract
1 - Introduction
2 - Motivations for strictly declarative rules
3 - Representation of knowledge in SDML
3.1 - Clauses
3.2 - Databases
3.3 - Rulebases
3.4 - Models
4 - Firing rules
4.1 - Forward chaining
4.2 - Compilation
4.3 - Dependencies and partitioning
4.4 - Optimising cycles in rulebases
4.5 - Backward chaining
5 - Assumption handling
5.1 - Creating assumptions
5.2 - Assumption tags
5.3 - Resolving assumptions
5.4 - Optimisations
5.4.1 - Partitioning
5.4.2 - Extending dependency graphs
5.4.3 - Ordering within partitions
5.4.4 - Invalid combinations of assumptions
5.4.5 - Validities
5.5 - Random and arbitrary decisions
6 - Performance
6.1 - Benchmarks
6.2 - Measurements
7 - Comparisons with other approaches
7.1 - Logic
7.2 - Truth maintenance systems
7.3 - Other declarative rule-based systems
8 - Conclusions
Acknowledgements
References

Efficient Forward Chaining for Declarative Rules in a Multi-Agent Modelling Language - 16 FEB 95
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