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Quantum affective processes for multidimensional decision-making.

Johnny K W Ho1, Johan F Hoorn2,3,4,5

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This study introduces Quantum Coppélia (Q-Coppélia), a quantum-computational framework for simulating robot affect. It addresses challenges in modeling ambiguous emotional states and parallel processing in human-robot interaction.

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Area of Science:

  • Artificial Intelligence
  • Quantum Computing
  • Cognitive Science

Background:

  • Modeling human affective systems for human-robot interaction presents challenges in handling ambiguous emotional states, probabilistic decisions, and parallel cognitive processes.
  • Conventional computation struggles with representing contextual behaviors and self-directed neuroplasticity, hindering realistic affective simulations.
  • Existing fuzzy-based systems like Silicon Coppélia offer a foundation but lack the theoretical capacity for quantum-level ambiguity and parallelism.

Purpose of the Study:

  • To develop a quantum-computational framework for simulating robot affect that can handle indefinite and ambiguous emotional states.
  • To address the limitations of conventional computation in modeling parallel cognitive processes and contextual aspects of behavior.
  • To translate fuzzy-based affective models into quantum logics for enhanced simulation capabilities in human-robot interaction.

Main Methods:

  • Developed Quantum Coppélia (Q-Coppélia) by translating the fuzzy-based Silicon Coppélia system into quantum logics.
  • Utilized quantum algorithms to represent and process ambiguous affective states and parallel cognitive functions.
  • Detailed the circuitry of the Q-Coppélia framework for simulating the progression of a robot's attitude towards a user.

Main Results:

  • Demonstrated the theoretical capability of Q-Coppélia to account for indefinite and ambiguous affective states.
  • Showcased the framework's ability to handle parallelism, a key feature of cognitive processes.
  • Provided a system for simulating affective interactions by linking quantum algorithms with psychological principles.

Conclusions:

  • Q-Coppélia offers a novel approach to simulating robot affect by leveraging quantum computation.
  • The framework theoretically supports the modeling of complex psychological phenomena like ambiguity and parallelism in affective states.
  • This work bridges quantum algorithms and psychology, paving the way for more sophisticated affective human-robot interaction.