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Designing Behavior Trees from Goal-Oriented LTLf Formulas
Temporal logic can be used to formally specify autonomous agent goals, but synthesizing planners that guarantee goal satisfaction can be computationally prohibitive.
Efficiently Evolving Swarm Behaviors Using Grammatical Evolution With PPA-style Behavior Trees
Evolving swarm behaviors with artificial agents is computationally expensive and challenging.
A brief history on Homomorphic learning: A privacy-focused approach to machine learning
In this paper, we trace back the ideas of homomorphic learning formally posed by Ronald L. Rivest and Len Alderman as "Can we compute upon encrypted data?"
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