EMBODIED INTELLIGENCE

1. Satpreet Arora (07d05003) Rachit Gupta (07d05008) Devendra Shelar (07d05010) Amrose Birani (07005003) EMBODIED INTELLIGENCE

2. Father of Embodied Intelligence • Rodney Brooks suggested the design of intelligent machines through interaction with the environment driven by perception and action, rather than by a pre-specified algorithm. • Brooks showed that robots could be more effective if they 'thought' (planned or processed) and perceived as little as possible.

3. Precursors of Embodied Intelligence • In the early stages of robotics robots were built on cybernetic principles. • Brooks proposed that vision and locomotion are the 2 primary needs of natural intelligence. • He proposed that environment is best model and not representation • These propositions revolutionized the way of thinking !!

4. The Rationale and Objectives “New Technologies and design approaches for building physically embodied intelligent agents and artefacts, with emphasis on the relationship between shape, function and the physical and social environment”

5. What is Embodied Intelligence • EmbodiedIntelligence(EI)is a mechanism that learns how to survive in a hostile environment • Mechanism: biological, mechanical or virtual agent with embodied sensors and actuators • EI acts on environment and perceives its actions • Hostility: direct aggression, pain, anxiety or scarcity of resources • EI learns so it must have associativeself-organizing memory Source: Ohio Univ CSE

6. Continued ... • It should have a purpose of being • it should maintain and pursue multiple goals, choosing which goal to implement based on the environmental conditions. • In addition, the complexity of a creature’s behavior would reflect the complexity of the environment in which it operates rather than its own. Source: Ohio Univ CSE

7. Waste Allocation Load Lifter – Earth Class • He is better known as Wall-e • He stays in a very hostile environment • reflects the complexity of the environment it stays in ! • Has an excellent purpose of being • Can collect garbage, repair his own tire and perform a lot more stuff  multiple goals !! • In nutshell  excellent example of embodied intelligence Source : Pixar Animations

8. How to create machine intelligence? Specialized Problems in AI • Knowledge Representation • Natural language and scene understanding • Semantic Cognition • Reinforcement Learning

9. Nature Vs Machines • It took nature over 3 billion years to create insects • 200 million more years to create mammals • 15 million years for the transformation of great apes to modern man about 3 million years ago • Major developments of the civilized world within the last 10,000 years. • It seems that in nature it is easier to append a primitive brain to create a complex brain. • While this may justify an approach in which a machine’s reflexes are developed first, the lack of a mechanism to add complexity at a low design cost is a major problem that cannot be left to chance.

10. ChallengesofEmbodiedIntelligence

11. Outline • Traditional Artificial Intelligence • Embodied Intelligence (EI) • Challenges of EI • We need to know how • We need means to implement it • We need resources to build and sustain its operation • Promises of EI • To economy • To society

12. Intelligence

13. Traditional AI Embodied Intelligence • Attempt to simulate “highest” human faculties like language, reasoning, problem solving • Brain is taken to be an abstract problem solver • Environment model based approach. Note that environment is extremely difficult to model. • Pre-specified problems are solved using abstract ways • knowledge is implicit in the fact that we have a body • Embodiment is a foundation for brain development • Intelligence develops through constant interaction with environment • Problems are identified and solved by goal seeking behavior Source : Ohio Univ

14. Design principles of intelligent systems Agent Source : Design Principles for Intelligent Systems Department of Information Technology, University of Zurich

15. Embodiment Intelligence core Environment Embodiment of Mind • Necessary for development of intelligence • Hosts brain’s interfaces that interact with environment • Not necessarily constant or in the form of a physical body • Boundary transforms modifying brain’s self-determination

16. Continued ... • Brain learns own body’s dynamic • Self-awareness results from identification with own embodiment • Embodiment can be extended by using tools and machines • Successful operation depends on correct perception of environment and own embodiment

17. The Brain • While we learn it’s functions can we emulate it’s operation ?

18. How can we design intelligence? • We need to know how • We need means to implement it • We need resources to build and sustain its operation Name: Dav Source: MSU Univ CSE

19. Requirements for Embodied Intelligence • State oriented • Learns spatio-temporal patterns • Situated in time and space • Learning • Perpetual learning • Screening for novelty • Value driven • Goal creation • Competing goals • Emergence • Artificial evolution • Self-organization

20. EI InteractionwithEnvironment Agent Architecture Reason Short-term Memory Perceive Act RETRIEVAL LEARNING Long-term Memory INPUT OUTPUT Task Environment Simulation or Real-World System

21. We need to develop .. • Sensory Interfaces • Active Vision • Speech Processing • Tactile, Smell, Taste, Temperature, Pressure Sensing • Additional Sensing • Infrared, Radar, Ultrasound, GPS, Etc. • Can Too Many Senses Be Less Useful? • Reinforcement Interfaces • Energy, Temperature, Pressure, Acceleration Level • Teacher Input • Motor Interfaces • Arms, Legs, Fingers, Eye Movement

22. Continued ... • Algorithmic Solutions For • Association, Memory, Sequence Learning, Invariance Building, Representation, Anticipation, Value Learning (Pain Reduction), Goal Creation, Planning • Circuits For Neural Computing • Determine Organization Of Artificial Minicolumn • Self-organized Hierarchy Of Minicolumns For Sensing And Motor Control • Self-organization Of Goal Creation Pathway Source : Univ. of Sussex Alastair Channon

23. Goal Driven Behavior • Goal driven behavior is one of the required elements of intelligence • Perceptions and actions are activated selectively to serve the machine’s objectives • In the existing EI models, the goal is defined by designers and is given to the learning agent • Humans and animals create their own goals • The goal creation may be one of the most important elements of EI mechanism Source: Janusz A. Starzyk -- Challenges of EI

24. Goal Creation • Goals must be built and understood in a similar way to building perceptions • complex goals can be understood only if representations are build • It should result from EI interaction with environment, by perceiving successes or failures of its actions • essential for developing intelligence • We will create goals based on simple structures interacting with sensory and motor pathways Source: Janusz A. Starzyk -- Challenges of EI

25. How can we design intelligence? • We need to know how • We need means to implement it • We need resources to build and sustain its operation

26. Doubling (or Halving) times • Clock speed 2.7 years • Dynamic RAM Memory “Half Pitch” Feature Size 5.4 years • Dynamic RAM Memory (bits per dollar) 1.5 years • Average Transistor Price 1.6 years • Microprocessor Cost per Transistor Cycle 1.1 years • Total Bits Shipped 1.1 years • Processor Performance in MIPS 1.8 years • Transistors in Intel Microprocessors 2.0 years • Microprocessor Clock Speed 2.7 years Source: Chemheritage.org, IEEE Explore IITB

27. Is It Possible ? • the area occupied by the new logic must be gradually reduced from over 60% in 1999 to less than 5% in 2010. • It is a way to shorten the design time, but it doesn’t create high-value designs !!! • Yet the structure of interconnections in human brain is very complex. • Thus a design of EI could be tremendously costly even if we know how to build it.

28. Promises of embodied intelligence • To society • Advanced use of technology • Robots • Tutors • Intelligent gadgets • Society of minds • Superhuman intelligence • Progress in science • Solution to societies’ ills • To industry • Technological development • New markets • Economical growth Name : Sail Source: MSU Univ CSE

29. Sounds like science fiction • If you’re trying to look far ahead, and what you see seems like science fiction, it might be wrong. • But if it doesn’t seem like science fiction, it’s definitely wrong. Name : Wall-E Source: Pixar Animations

30. Thank You

31. References • Motivation in Embodied Intelligence (2005)– janusz Starzyk (Ohio Univ. USA) • Challenges of Embodied Intelligence (2001) - Janusz A. Starzyk, Yinyin Liu, and Haibo He (Ohio Univ. USA) • Moravec, H.P. (1999) -- Rise of the Robots  • Pixar Animations  http://www.pixar.com/featurefilms/walle/ • The Evolutionary Emergence route to Artificial Intelligence -- Alastair Channon (UNIVERSITY OF SUSSEX 1995-96) • Design Principles for Intelligent Systems (2003)  Rolf Pfeifer1, Fumiya Iida1, Josh Bongard2 Department of Information Technology, University of Zurich • Michigan State Univ. http://www.cse.msu.edu/ei/ • Chemheritage.org & IEEE Explore IITB • Wikipedia