The society of mind
Understanding fault-tolerant distributed systems
Communications of the ACM
ACM SIGART Bulletin
An autonomous spacecraft agent prototype
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Adaptive Intrusion Detection: A Data Mining Approach
Artificial Intelligence Review - Issues on the application of data mining
FERNN: An Algorithm for Fast Extraction of Rules fromNeural Networks
Applied Intelligence
Machine Learning
Architecture for an Artificial Immune System
Evolutionary Computation
Robust agent teams via socially-attentive monitoring
Journal of Artificial Intelligence Research
Eurisko: A program that learns new heuristics and domain concepts
Artificial Intelligence
Learning plan transformations from self-questions: a memory-based approach
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
The well-designed young mathematician
Artificial Intelligence
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In a hostile environment, an autonomous cognitive system requires a reflective capability to detect problems in its own operation and recover from them without external intervention. We present an architecture in which reflection is distributed so that components mutually observe and protect each other, and where the system has a distributed model of all its components, including those concerned with the reflection itself. Some reflective (or 'meta-level') components enable the system to monitor its execution traces and detect anomalies by comparing them with a model of normal activity. Other components monitor 'quality' of performance in the application domain. Implementation in a simple virtual world shows that the system can recover from certain kinds of hostile code attacks that cause it to make wrong decisions in its application domain, even if some of its self-monitoring components are also disabled.