Presentation is loading. Please wait.

Presentation is loading. Please wait.

Bio-Inspired Computing Overview & Biased History Based on presentation by Netta Cohen from University of Leeds.

Similar presentations

Presentation on theme: "Bio-Inspired Computing Overview & Biased History Based on presentation by Netta Cohen from University of Leeds."— Presentation transcript:


2 Bio-Inspired Computing Overview & Biased History Based on presentation by Netta Cohen from University of Leeds

3 2 What is Bio-Inspired Computing all about? Biological computation Artificial Intelligence Bio-inspired computing

4 3 The First Computer Charles Babbage ( ): Inventor of difference engine – recognised as direct ancestor of the modern computer. First (non-biological) digital machine.

5 4 How bioinspired computing works? Autonomous cells Messages (data, sender & receiver addresses) Operations (contained in message) Cell differentiation (context-dependent functionality ) What good is this? ‘Building’ programs the way civil engineers design buildings. programmers can create objects to mimic generic conceptual building blocks: No need for a new language with each application.

6 5 AI programming Bioinspired programming stands in stark contrast to familiar AI programming languages. In 1959, John McCarthy suggested a programming language with common sense. Lisp (List Processing): logical operations represented as manipulations of lists. Even functions and procedures are defined as lists. McCarthy’s goal in designing Lisp was - and still is - “to make a machine that would be as intelligent as a human.” Common sense: the ability to deduce for one’s self a sufficiently wide class of consequences based on available information.

7 6 Good solutions benefit from appropriate representations. Good solutions rely on appropriate heuristics (rules of thumb). Principles of AI These principles date from AI’s earliest beginnings… The Symbolic Search Hypothesis: “A physical symbol system exercises its intelligence in problem solving by search – that is, by generating and progressively modifying symbol structures until it produces a solution structure.”

8 7 The Birth of AI In the 1940s Alan Turing was already speculating on… Artificial Intelligence is an attempt to simulate reasoning as: abstract, formal, disembodied, symbol manipulation. 1.…the possibility of general computer intelligence – abstract games: good initial tasks ‘requiring little contact with the outside world’… 2.…the potential for a computer chess player – search algorithms to used to find good moves… 3.…a way of deciding whether a computer was intelligent – the Turing Test is a totally disembodied interrogation (but a somewhat situated one)…

9 8 “Intelligence w/out Reason” Rodney Brooks (“Intelligence Without Reason”): Critic of the AI approach & strong proponent of embodiment and situatedness in bioinspired computing (BIC). AI, he claims, followed the abstract route due to technological gaps in the 40s & 50s. Today, he says, it’s time to move on. Brooks recognised that life-like systems are often intelligent to some degree, yet reasoning is primarily considered to be a human attribute. Rather than modelling complicated human behaviour, why not start simple?

10 9 Why Not The Whole Iguana? Traditional computing is task-oriented (vertical). To survive, animals have to be good across the board! Ant Cricket Iguana Human WalkingSexMemoryChess Horizontal Vertical Rather than build parts of human intelligence, why not build an entire much simpler intelligence?

11 10 AI vs BIC Overlap between AI and BIC is considerable, but there are also distinctions. BIC might be the follower of AI. However, it could also be regarded as a rebel. building life-like systems (utilising cartoon models of biological systems, tasks & concepts). using them to improve our understanding of biology BIC building (esp. human-like) intelligent machines with common sense & decision making that naively belies deductive logic. using them to improve our understanding of human intelligence. AI

12 11 SHRDLU By 1972, Terry Winograd’s invented a simulated robot arm surrounded by blocks of various shapes and colours on a table. SHRDLU could… In Winograd’s words, it was “a computer program which ‘understands’ language in a limited domain.” SHRDLU’s algorithms carried out model building, search, planning and logical deduction. understand natural language instructions ask questions to disambiguate these instructions act & reason in a simulated “blocksworld” environment answer questions about the world & its own reasoning See for example:

13 12 A Conversation with SHRDLU (adapted from Dreyfus’ 1979 What Computers Can’t Do) > Pick up a big red block. OKAY. > Grasp the pyramid. I DON’T KNOW WHICH PYRAMID YOU MEAN. > What does the box contain? THE BLUE PYRAMID AND THE BLUE BLOCK. > I own blocks which are not red, but I don’t own anything which supports a pyramid. I UNDERSTAND. > Do I own the box? NO.

14 13 Is that really how our brain works? John Von Neumann, father of modern high-speed computers also thought about neuro-computation and tried, for the first time, to construct a meaningful comparison between brain and computer power. Von Neumann argued that the brain must employ digital computation. Figuring in the number of neurons, connections, and estimates of computational speed and statistical noise in the brain, he then concluded that the brain could not be explained by logic alone. In fact, he apparently postulated (and began writing) an alternative theory but died soon after.

15 14 “The Language of the Brain is Not the Language of Mathematics … whatever language the central nervous system is using, it is characterized by less logical and arithmetical depth than what we are normally used to … Consequently, there exist here different logical structures from the ones we are ordinarily used to... … whatever the system is, it cannot fail to differ considerably from what we consciously and explicitly consider as mathematics.” (John Von Neumann, The Computer and the Brain, 1958.) The manuscript (published post mortem) ends as follows: “Von Neumann challenged the validity of the underlying conceptualizations we use to study the brain and compare it with computers. Yet, what is surprising, given the great esteem for John Von Neumann, is that no one has taken up on his argument and fully developed its consequences in the mind versus artificial intelligence arguments that had been waging the last few years.” In a recent commentary, Harold Morowitz writes:

16 15 Chess vs. Football Chess Discrete Full Information Single Opponents Turn Taking Limited Options per Turn Intellectual, disembodied Optimal Strategy Exists? Demands General Intelligence? Formal, Analytical, Symbolic Can the problems faced by footballers be solved through symbol processing and heuristic search? Football Continuous Partial Information Heterogeneous Teams Continuous Confrontation Unlimited Options Physical, embodied No Optimal Strategy? Demands Specialist Skills? Dynamic, Physical, Reactive

17 16 Autonomous Mobile Robots 1990s: roboticists turn to building simple, robust, insect- like robots geared towards performing tasks that belie their mediocre brains. Brooks’ autonomous mobots embody the new philosophy: – embedded, embodied, and unencumbered by intellect – “fast, cheap, and out of control” Recent developments

18 17 Take home message... Biological computation Artificial Intelligence Bio-inspired computing or What is BIC and what does it want to achieve?

19 18 Additional Papers “Intelligence without reason” – Brooks (1991). Popular Reading “ John McCarthy: The uncommon logician of common sense”, in Shasha & Lazere (1995). “Alan Kay: A clear romantic vision”, ibid. “Computers and Brains”, in Morowitz (1997). At home Reading Set-up BEAST. Instructions can be found on:

20 19 BIC Structure Key Topics include –Artificial neural networks –Evolutionary design and genetic algorithms –Co-evolutionary design –Multi-agent systems and swarm Intelligence –Artificial life –Robotics and control –Interfacing biology with silicon

21 20 Some basics Think, read, ask questions, tinker, and have fun! Warning: Some of the material covered is, or recently was, cutting edge. There will be programming, some biology, some philosophy. There is a lot of material to cover, but… lecture slides will not tell the whole story. You should install and familiarise yourself with the module courseware – BEAST – starting NOW. Show enthusiasm, play, contribute original code. Originality and innovation will be rewarded.

22 21 Resources Course Website: –Lecture Slides –Reading Lists –Assignments –Useful Links Each other –Talk about the material. –Talk about the assignments. –Help each other; feel free to work together, but –Submit only you own personal original work. Newsgroups: local.modules.ai23 Reading available in library, or via links on course page.

Download ppt "Bio-Inspired Computing Overview & Biased History Based on presentation by Netta Cohen from University of Leeds."

Similar presentations

Ads by Google