Declarative Logic-Based Pareto-Optimal Agent Decision Making

Tonmoay Deb, Mingi Jeong, Cristian Molinaro, Andrea Pugliese, Alberto Quattrini Li, Eugene Santos, V. S. Subrahmanian, Youzhi Zhang

Research output: Contribution to journalArticlepeer-review


There are many applications where an autonomous agent can perform many sets of actions. It must choose one set of actions based on some behavioral constraints on the agent. Past work has used deontic logic to <italic>declaratively</italic> express such constraints in logic, and developed the concept of a feasible status set (FSS), a set of actions that satisfy these constraints. However, multiple FSSs may exist and an agent needs to choose one in order to act. As there may be many different objective functions to evaluate status sets, we propose the novel concept of <italic>Pareto-optimal FSSs</italic> or . We show that checking if a status set is a is co-NP-hard. We develop an algorithm to find a and in special cases when the objective functions are monotonic (or anti-monotonic), we further develop more efficient algorithms. Finally, we conduct experiments to show the efficacy of our approach and we discuss possible ways to handle multiple Pareto-optimal Status Sets.

Original languageEnglish (US)
Pages (from-to)1-16
Number of pages16
JournalIEEE Transactions on Cybernetics
StateAccepted/In press - 2024


  • Automobiles
  • Autonomous agents
  • Coolants
  • intelligent agents
  • Linear programming
  • logic
  • Optimization
  • Roads
  • Safety
  • Uncertainty

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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