Bled, October 28-30, 2004 Mind RACES: from Reactive to Anticipatory Cognitive Embodied Systems Rino Falcone Institute of Cognitive Sciences and Technologies.

Slides:



Advertisements
Similar presentations
Approaches, Tools, and Applications Islam A. El-Shaarawy Shoubra Faculty of Eng.
Advertisements

Cognitive Systems, ICANN panel, Q1 What is machine intelligence, as beyond pattern matching, classification and prediction. What is machine intelligence,
1 NEST New and emerging science and technology EUROPEAN COMMISSION - 6th Framework programme : Anticipating Scientific and Technological Needs.
ARCHITECTURES FOR ARTIFICIAL INTELLIGENCE SYSTEMS
Improving System Safety through Agent-Supported User/System Interfaces: Effects of Operator Behavior Model Charles SANTONI & Jean-Marc MERCANTINI (LSIS)
Chapter Thirteen Conclusion: Where We Go From Here.
Bologna Process in terms of EU aims and objectives
University of Minho School of Engineering Centre ALGORITMI Uma Escola a Reinventar o Futuro – Semana da Escola de Engenharia - 24 a 27 de Outubro de 2011.
AI 授課教師:顏士淨 2013/09/12 1. Part I & Part II 2  Part I Artificial Intelligence 1 Introduction 2 Intelligent Agents Part II Problem Solving 3 Solving Problems.
Faculty of Management and Organization Emergence of social constructs and organizational behaviour How cognitive modelling enriches social simulation Martin.
Intelligence without Reason
Provisional draft 1 ICT Work Programme Challenge 2 Cognition, Interaction, Robotics NCP meeting 19 October 2006, Brussels Colette Maloney, PhD.
Overview and History of Cognitive Science. How do minds work? What would an answer to this question look like? What is a mind? What is intelligence? How.
INTRODUCTION. Concepts HCI, CHI Usability User-centered Design (UCD) An approach to design (software, Web, other) that involves the user Interaction Design.
Noynay, Kelvin G. BSED-ENGLISH Educational Technology 1.
Systems Engineer An engineer who specializes in the implementation of production systems This material is based upon work supported by the National Science.
Biointelligence Laboratory School of Computer Science and Engineering Seoul National University Cognitive Robots © 2014, SNU CSE Biointelligence Lab.,
Vedrana Vidulin Jožef Stefan Institute, Ljubljana, Slovenia
THEORIES OF MIND: AN INTRODUCTION TO COGNITIVE SCIENCE Jay Friedenberg and Gordon Silverman.
Cognitive Psychology, 2 nd Ed. Chapter 1. Defining Cognitive Psychology The study of human mental processes and their role in thinking, feeling, and behaving.
Introduction to Computer and Programming CS-101 Lecture 6 By : Lecturer : Omer Salih Dawood Department of Computer Science College of Arts and Science.
ICEE 2005GLIWICE, POLAND JULY 2005 FEDERAL CENTER OF TECHNOLOGICAL EDUCATION – CEFET-RJ – BRAZIL PRODUCTION ENGINEERING DEPARTMENT CSCW: A FORMATION.
Introduction to Behavior- Based Robotics Based on the book Behavior- Based Robotics by Ronald C. Arkin.
Chapter 14: Artificial Intelligence Invitation to Computer Science, C++ Version, Third Edition.
Mind RACES from Reactive to Anticipatory Cognitive Embodied Systems Our Objectives The general goal of Mind RACES is to investigate different anticipatory.
CSC – School of Computer Science and Communication.
An Architecture for Empathic Agents. Abstract Architecture Planning + Coping Deliberated Actions Agent in the World Body Speech Facial expressions Effectors.
Cognitive Reasoning to Respond Affectively to the Student Patrícia A. Jaques Magda Bercht Rosa M. Vicari UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL BRASIL.
TEA Science Workshop #3 October 1, 2012 Kim Lott Utah State University.
A RTIFICIAL I NTELLIGENCE Introduction 3 October
Artificial Intelligence Introductory Lecture Jennifer J. Burg Department of Mathematics and Computer Science.
UW Contributions: Past and Future Martin V. Butz Department of Cognitive Psychology University of Würzburg, Germany
Towards Cognitive Robotics Biointelligence Laboratory School of Computer Science and Engineering Seoul National University Christian.
Prediction in Human Presented by: Rezvan Kianifar January 2009.
Integrating high- and low-level Expectations in Deliberative Agents Michele Piunti - Institute of.
Beyond Gazing, Pointing, and Reaching A Survey of Developmental Robotics Authors: Max Lungarella, Giorgio Metta.
1 NEST New and emerging science and technology EUROPEAN COMMISSION - 6th Framework programme : Anticipating Scientific and Technological Needs.
IST Contribution lisbon Mind Races meeting, September 2005.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
The roots of innovation Future and Emerging Technologies (FET) Future and Emerging Technologies (FET) The roots of innovation Proactive initiative on:
EU Project MACS Multi-sensory Autonomous Cognitive Systems Interacting with Dynamic Environments for Perceiving and Using Affordances Erich Rome Robot.
Roma, Meeting Mindraces 2-3 October 2006 ISTC-CNR Achievements MindRACES: From Reactive to Anticipatory Cognitive Embodied Systems (FP )
New Bulgarian University MindRACES, First Review Meeting, Lund, 11/01/2006 Anticipation by Analogy An Attempt to Integrate Analogical Reasoning with Perception,
CSE 102 Introduction to Computer Engineering What is Computer Engineering?
Digital Libraries1 David Rashty. Digital Libraries2 “A library is an arsenal of liberty” Anonymous.
What is Artificial Intelligence?
MindRACES, First Review Meeting, Lund, 11/01/ Anticipatory Behavior for Object Recognition and Robot Arm Control Modular and Hierarchical Systems,
Introduction to HCI Lecture #1.
RULES Patty Nordstrom Hien Nguyen. "Cognitive Skills are Realized by Production Rules"
WP6 - D6.1 Design of integrated models ISTC-CNR September, 26/27, 2005 ISTC-CNR September, 26/27, 2005.
Artificial Intelligence: Research and Collaborative Possibilities a presentation by: Dr. Ernest L. McDuffie, Assistant Professor Department of Computer.
Artificial Intelligence Chapter 1 - Part 2 Artificial Intelligence (605451) Dr.Hassan Al-Tarawneh.
Cognitive Science Overview Introduction, Syllabus
Intelligent Control Methods Lecture 2: Artificial Intelligence Slovak University of Technology Faculty of Material Science and Technology in Trnava.
WP6 Emotion in Interaction Embodied Conversational Agents WP6 core task: describe an interactive ECA system with capabilities beyond those of present day.
Cognitive Modeling Cogs 4961, Cogs 6967 Psyc 4510 CSCI 4960 Mike Schoelles
Overview of Artificial Intelligence (1) Artificial intelligence (AI) Computers with the ability to mimic or duplicate the functions of the human brain.
Wuerzburg, April 20-21, 2006 Fifth Meeting of Mind RACES: State of the Art Rino Falcone - Project Coordinator Institute of Cognitive Sciences and Technologies.
ISTC-CNR contribution to D2.2
What is cognitive psychology?
Anticipation and Emotion: a low-level approach to Believability
Scenario Specification and Problem Finding
CHAPTER 1 Introduction BIC 3337 EXPERT SYSTEM.
Overview of Year 1 Progress Angelo Cangelosi & ITALK team
Mind RACES: some Emerging Challenges
Bioagents and Biorobots David Kadleček, Michal Petrus, Pavel Nahodil
Introduction Artificial Intelligent.
Engineering Autonomy Mr. Robert Gold Director, Engineering Enterprise
CHAPTER I. of EVOLUTIONARY ROBOTICS Stefano Nolfi and Dario Floreano
LEARNER-CENTERED PSYCHOLOGICAL PRINCIPLES. The American Psychological Association put together the Leaner-Centered Psychological Principles. These psychological.
Presentation transcript:

Bled, October 28-30, 2004 Mind RACES: from Reactive to Anticipatory Cognitive Embodied Systems Rino Falcone Institute of Cognitive Sciences and Technologies National Research Council of Italy Rome Cognitive Systems Kickoff Bled, Slovenia October 28-30, 2004

Bled, October 28-30, 2004 General Information Title: Mind RACES - from Reactive to Anticipatory Cognitive Embodied Systems Start Date: 1 October 2004 Duration: 36 months (till September 2007) EC Contribution: euros Coordinator: Institute of Cognitive Sciences and Technologies (National Research Council of Italy) Consortium: 1) ISTC-CNR (Italy), 2) Lunds Universitet (Sweden) 3) Bayerische Julius-Maximilians Universitaet Wuerzburg (Germany) 4) New Bulgarian University (Bulgaria) 5) Instituto Superior Técnico (Portugal) 6) Oesterreichische Studiengesellschaft Fuer Kybernetik (Austria) 7) Scuola Universitaria Professionale della Svizzera Italiana (Switzerland) 8) Noze s.r.l. (Italy)

Bled, October 28-30, 2004 Context and Relevance of the Project The major claim of Mind RACES: in order to be successfully autonomous, to deal with novel, dynamic, and trustworthy environments, such robots and devices need to have sophisticated cognitive capabilities based on anticipation Only a cognitive system with anticipation mechanisms can be credible, adaptive and successful in interaction with the environment and in social interaction with other cognitive systems and with humans Future IT systems will be intimately integrated with everyday environments, both as stand-alone objects or software entities then We have to consider new challenging scenarios with a set of interaction problems among man, environment, autonomous robots and embedded smart devices

Bled, October 28-30, 2004 Cognitive Systems and Anticipation From the Objective of the 'Cognitive Systems’ Action Line : “To construct physically instantiated or embodied systems that can perceive, understand and interact with their environment, and evolve in order to achieve human-like performance in activities requiring context- (situation and task) specific knowledge” It is really difficult to think about systems performing like (and interacting with) humans without any mechanism of anticipation

Bled, October 28-30, 2004 Definitions of Anticipation 1. An anticipatory system is a system containing a predictive model of itself and/or of its environment that allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant. (Robert Rosen) 2. An anticipatory system is a system whose current state is determined by a future state. The cause lies in the future (Robert Rosen, Heinz von Foerster) 3. Anticipation is a process of co-relation among factors pertaining to the present, past and future of a system (Mihai Nadin) 4. Anticipation is the expression of natural entailment (Robert Rosen) 5. Feedforward and inverse kinetics are part of the integrated mechanism of anticipation (Daniel Dennett, Daniel Wolpert, Mihai Nadin) For more references:

Bled, October 28-30, 2004 Explicit and Implicit Anticipation Explicit Anticipation The organism/system is able to generate “representations” of the forthcoming events at different time scales Case1. A real expectation built on a mental model of a future event like in planning, intentional behavior, hopes etc… (mental anticipation) Case2. “Expectations” in the anticipatory classifiers (the sensory- motor representation of future effects of actions) Not all anticipatory behavior is based on explicit representations of future events (expectations) Implicit Anticipation or merely behavioral anticipation The response is associated with a stimulus (a precursor) The behavior is selected to react to the event that is forthcoming (preparatory behavior) Ex. A grasshopper jumps at a rustle “to” avoid the predator not as a reaction to the noise itself Ex. The bodily activation of emotions is preparatory for the “escaping” behavior.

Bled, October 28-30, 2004 MindRACES Goal The general goal of the Mind RACES project is to investigate different anticipatory cognitive mechanisms and architectures and their functionalities in order to build Cognitive Systems endowed with the ability: - to predict the outcome of their actions, - to build a model of future events, - to control their perception anticipating future stimuli and - to emotionally react to possible future scenarios Such Anticipatory Cognitive Systems will contribute to the successful implementation of the new ambient intelligence

Bled, October 28-30, 2004 Four Distinct Objectives The project : 1) will identify typologies of problems which require different anticipatory cognitive capabilities; this will allow to design and implement different appropriate scenarios 2) will improve existing anticipatory architectures and will incorporate missing anticipatory functionalities in them. The performances of these architectures will be tested in the scenarios 3) will compare in the same scenarios anticipatory architectures implemented from different theoretical backgrounds 4) will design, implement and test in the scenarios the cognitive architectures that integrate different kind of anticipatory mechanisms. Both simulations and real robots will be used to improve and compare single anticipatory models and to integrate them in the same cognitive architectures.

Bled, October 28-30, 2004 Cognitive Functions Attention, Monitoring and Control (Work Package 3) Anticipatory mechanisms: Expectation-based attention shifting, attention as epistemic control, constructive perception - Epistemic Actions are actions aimed at acquiring new information from the environment usually through the shift of the attentional focus and its fixation which determines what the cognitive system will perceive Goal directed behaviour, Pro-activity and Analogy (Work Package 4) Anticipatory mechanisms: Sub-symbolic planning, pro-active activation of goals, anticipation at different time scales and levels of abstractions (for instance, anticipatory classifiers), construction of models of future events based on analogy. - Cognitive Systems need to select their own actions with a set of different mechanisms: from simple reactions based on future rewards to higher level proactive reasoning on an explicit model of the future Anticipatory Emotions (Work Package 5) Anticipatory mechanisms: goals activation based anticipatory affective states (somatic markers), affective monitoring of goals’ satisfaction, appraisal of future events on the basis of perceived signs - Anticipatory character of the emotional response (fear, hope, anxiety)

Bled, October 28-30, 2004 Expected Results A potential relevant contribution will be provided by assembling in a credible and efficient way different anticipatory layers and mechanisms implementing several cognitive functions An important Goal is to design a visible advance of conception for the Cognitive System Architectures, where either through layers, or through modularity, or through hybrid composition, different cognitive mechanisms for anticipating and dealing with the environmental changes will be assembled in a biologically and psychologically principled and efficient way

Bled, October 28-30, 2004 Expertise of the Consortium The Mind RACES consortium has been composed with partners that are expert in different scientific disciplines and complementary approaches to anticipation: - The Psychology of Action (ISTC-CNR and UW-COGSCI) - Experimental Psychology (NBU) - Situated and Evolutionary Robotics (LUCS, ISTC-CNR, IDSIA-SUPSI, OFAI) - Artificial Intelligence and Cognitive Modelling (OFAI, ITSC-CNR, NBU) - Mathematics and Adaptive Robotics (IDSIA-SUPSI) - Affective Computing and Human Computer Interaction (IST)

Bled, October 28-30, 2004 ISTC-CNR (coordinator) The National Research Council (Consiglio Nazionale delle Ricerche) of Italy’s Institute of Cognitive Sciences and Technologies (first called Institute of Psychology) was officially created in Relevant Expertise: two groups (Artificial Intelligence Group and the Group on Artificial Life and Robotics); neural networks, BDI models, Cognitive theory of emotions, evolutionary robotics Scientific Leaders: Cristiano Castelfranchi, Rino Falcone, Stefano Nolfi

Bled, October 28-30, 2004 Lunds Universitet Lunds Universitet, with seven faculties and a number of research centres and specialized institutes, is the largest unit for research and higher education in Sweden. It was founded in 1666 Relevant Expertise: robotics, connectionist systems, attention driving Scientific Leader: Christian Balkenius

Bled, October 28-30, 2004 UW- Department of Cognitive Psychology The Institute of Psychology at the Bayerische Julius-Maximilians Universitaet Wuerzburg was founded more than a hundred years ago in Over the following years, the so-called Würzburg-school of psychology laid out the foundations for the investigation of complex thought processes and particularly an experimental approach to the investigation of higher level cognition. Relevant Expertise: Formal and Computational Models of anticipatory mechanisms, Anticipatory Classifiers Systems Scientific Leaders: Joachim Hoffman, Martin Butz

Bled, October 28-30, 2004 New Bulgarian University The Central and East European Center for Cognitive Science is an interdisciplinary research Center at NBU bringing together researchers in computer science, psychology, neurosciences, linguistics, and philosophy. Relevant Expertise: Formal and Computational Models of Analogy, hybrid cognitive architectures Scientific Leaders: Maurice Greenberg, Boicho Kokinov

Bled, October 28-30, 2004 Instituto Superior Técnico IST (Instituto Superior Técnico) is a large Engineering Faculty of the Technical University of Lisbon created in The research and development activities at Instituto Superior Técnico are mainly carried out within Institutes, Departments, Centers and research Groups that integrate teaching and research staff allocated to the various departments of IST. Relevant Expertise: Formal and Computational Models of Emotions Scientific Leader: Ana Paiva

Bled, October 28-30, 2004 Oesterreichische Studiengesellschaft Fuer Kybernetik (OFAI) OFAI was founded in 1984 with support from the Austrian Federal Ministry for Science and Research. Relevant Expertise: Robotics, Connectionist Models Scientific Leader: Georg Dorffner

Bled, October 28-30, 2004 Scuola Universitaria Professionale della Svizzera Italiana (IDSIA-SUPSI) IDSIA-SUPSI's research focuses on optimal universal search algorithms, artificial neural nets, universal reinforcement learners and predictors, complexity and generalization issues, unsupervised learning and information theory, forecasting, artificial ants, combinatorial optimisation, evolutionary computation. IDSIA-SUPSI is small but visible, competitive, and influential. Relevant Expertise: Optimal mechanisms and algorithms for prediction and techniques for predicting at different levels of abstraction Scientific Leader: Juergen Schmidhuber

Bled, October 28-30, 2004 Noze S.r.l. Noze s.r.l. is a small and very dynamic Italian enterprise (SME) that offers state-of-the-art solutions in the Information and Communication Technology field, coupling competence, innovation and affordability. Relevant Expertise: Communication infrastructures, Dissemination, Artificial Intelligence Systems Leader: Fabio Adezio

Bled, October 28-30, 2004 Work Package Leaders Attention, Monitoring and Control Goal Directed Behaviour, Pro-activity and Analogy Anticipatory Emotions Integration Scenarios design and implementation Analysis of Anticipatory Mechanisms Prototypes NBU ISTC- CNR LUCS ISTUW- COGSCI

Bled, October 28-30, 2004 Conclusions MindRACES will investigate various forms and mechanisms of anticipation their adaptive functions the transition from one to the other the co-existence in complex systems (architectural problem)