BICA 2015

2015 Annual International Conference on Biologically Inspired Cognitive Architectures
Lyon, France, 06/11/2015–08/11/2015

<p>Biologically Inspired Cognitive Architectures (BICAs) are computational frameworks for building intelligent agents that are inspired by biological intelligence. These agents serve both as theoretical models (e.g., in cognitive science, neuroscience, economics and social sciences), and as intelligent controllers for autonomous systems (robots, games characters, smart human/machine interfaces, health applications, etc).</p>

<p>Biological intelligent systems (animals, including humans) have many qualities that are often lacking in artificially designed systems; their purpose goes beyond interacting with a closed environment or solving predefined logical problems. At the time when our understanding of natural intelligence is exploding, thanks to modern brain imaging, ethological studies, and the development of cognitive models mapping brain structures with functions, our ability to learn lessons from nature and to build biologically inspired intelligent systems has never been greater. At the same time, the growth in computer science and technology has unleashed enough design creativity and computational power to generate an explosion of applications in multiple domains.</p>

<p>Research in Biologically Inspired Cognitive Architectures contributes to the development of these applications by addressing the numerous questions raised by the problem of replicating natural intelligence – specifically, the complexity of higher cognitive abilities of the human mind – in an artificial system (widely known as the BICA Challenge). These questions are trans-disciplinary in nature and promise to yield multi-directional flow of understanding between all the involved disciplines.</p>

topics of interest
  • Neuroscience
    • “B” in BICA: useful biological constraints for cognitive architectures
    • Bridging the gap between artificial and natural information processing
    • Cognitive and learning mechanisms informed by neuroscience
    • Neural correlates of cognitive and meta-cognitive processes
    • Robustness, scalability and adaptability in neuromorphic systems
    • Neurophysiological underpinnings of reinforcement learning
    • Physiological mechanisms of memory formation and (re)consolidation
    • Representation of contextual and conceptual knowledge in neural systems
  • Social, Economic and Educational Sciences
    • Mixed-initiative systems based on inspirations from biology
    • Agents possessing human-level social, narrative, and emotional intelligence
    • BICA in pedagogical, learning, and tutoring technologies and education
    • BICA models of self and their application to self-aware perception and action
    • Representation, perception, understanding, processing and expression of emotions
    • Virtual characters and narratives, artificial personalities and human-compatibility of BICA
    • Agent-based modeling of intelligent social phenomena (are there any?)
    • Applications of BICA technologies in elderly care
  • Cognitive Science
    • Perception, reasoning, decision making and action in BICA
    • Combining natural and artificial approaches to cognition
    • Comparison of different forms of learning, memory, and cognitive growth
    • Theory-of-Mind, episodic and autobiographical memory in cognitive systems
    • Introspection, metacognitive reasoning and self-awareness in BICA
    • Models of learning and memory: robustness, flexibility, transferability
    • Natural and body language and its role in intelligence, cognition and interaction
    • Unifying frameworks and constraints for cognitive architectures: the grand unification
  • Artificial Intelligence
    • Creativity, goal reasoning and human-level autonomy in artifacts
    • Embodied vs. ambient intelligence: embedding or embodiment?
    • Natural Language capabilities and social competence of BICA
    • Learning by reading, by observation, by reasoning and by analogy
    • Robust and scalable machine learning mechanisms in BICA
    • Self-regulated learning, bootstrapped and meta-learning and the critical mass
    • The place for BICA in tomorrow's textbook of artificial intelligence
  • General
    • Mathematical basis for BICA and fundamental theoretical questions in BICA research
    • Alternative substrates for implementation of BICA: smart materials, quantum and biocomputing
    • Alternative approaches to the development of BICA: evolutionary, system-theoretic, educational
    • Fundamental academic, practical and theoretical questions in BICA research and technology
    • Cognitive Decathlon and Grand Challenges for BICA as components of the BICA Challenge
    • Critical mass for a universal human-level learner and a roadmap to solving the BICA Challenge
    • Metrics, tests, proximity measures and the roadmap to human-level / human-compatible AI
    • Leveraging the cloud, world-wide-web, and social-media: possible role for BICA?
    • Cybersecurity and secure authentication methods based on BICA
    • Interdisciplinary research opportunities involving BICA
    • International trends and opportunities in funding BICA related research