Presentation on theme: "Will Androids Dream of Electric Sheep? A Glimpse of Current and Future Developments in Artificial Intelligence Henry Kautz Computer Science & Engineering."— Presentation transcript:
Will Androids Dream of Electric Sheep? A Glimpse of Current and Future Developments in Artificial Intelligence Henry Kautz Computer Science & Engineering University of Washington
What is Artificial Intelligence? The study of the principles by which natural or artificial machines manipulate knowledge: –how knowledge is acquired –how goals are generated and achieved –how concepts are formed –how collaboration is achieved
... Exactly what the computer provides is the ability not to be rigid and unthinking but, rather, to behave conditionally. That is what it means to apply knowledge to action: It means to let the action taken reflect knowledge of the situation, to be sometimes this way, sometimes that, as appropriate.... -Allen Newell
Classical AI The principles of intelligence are separate from any hardware / software / wetware implementation –logical reasoning –probabilistic reasoning –strategic reasoning –diagnostic reasoning Look for these principles by studying how to perform tasks that require intelligence In general: divide and conquer!
Success Story: Medical Expert Systems Mycin (1980) –Expert level performance in diagnosis of blood infections Today: 1,000’s of systems –Everything from diagnosing cancer to designing dentures –Often outperform doctors in clinical trials –Major hurdle today – non-expert part – doctor/machine interaction
Success Story: Chess I could feel – I could smell – a new kind of intelligence across the table - Kasparov Examines 5 billion positions / second Intelligent behavior emerges from brute-force search
Is that all there is? The success stories of classical AI are based on automating the step-by- step rules of logic or probability theory But what about the importance of intuition, hunches, lucky guesses in natural intelligence?
Stochastic Inference Recent research on ways to solve problems that are inherently too big to solve by systematic search Idea: guess at a solution, then randomly perturb it until it “fits” We can illustrate such an approach on the N-Queens problemN-Queens problem
Intelligent Robotics In the 1990’s there was a growing concern that work in classical AI ignored crucial scientific questions: –How do we integrate the components of intelligence (e.g. learning & planning)? –How does perception interact with reasoning? –How does the demand for real-time performance in a complex, changing environment affect the architecture of intelligence?
Provide a standard problem where a wide range of technologies can be integrated and examined By 2050, develop a team of fully autonomous humanoid robots that can win against the human world champion team in soccer.
Robocup Insights Reactivity more important than optimal decision making Complex group behavior (e.g. passing) can be generated by surprisingly simple rules Can trade mechanical engineering for computing and vice-versa Highlights of 2002
“Cyborgs”: Fusing Animal and Machine Intelligence A different criticism of Classical AI is that to understand intelligence we must understand the brain, not just tasks Neural Nets – model of computation inspired by brain –massive number of simple parallel processing units –trained rather than programmed
Neural Net Success Stories Voice and character recognition Face recognition Modeling neural systems of animals UW Implantable Electronics Project The compelling scientific reason for this research is to correlate neuronal signaling and control with environmental stimuli and behavior, to better understand the neural substrates of behavior
Predictions Key future AI application: Helping take care of our aging population –robot nurses, rather than soccer players Key research future issue: cooperative intelligence –how the combination of a human and AI system can be more than the sum of its parts
… In sum, technology can be controlled especially if it is saturated with intelligence to watch over how it goes, to keep accounts, to prevent errors, and to provide wisdom to each decision. -Allen Newell