steps toward an agi roadmap włodek duch ( google: w. duch) agi, memphis, 1-2 march 2007 roadmaps: a...
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Steps Toward an AGI RoadmapSteps Toward an AGI RoadmapSteps Toward an AGI RoadmapSteps Toward an AGI Roadmap
Włodek DuchWłodek Duch ( (Google: Google: W. W. DuchDuch))
AGI, Memphis, 1-2 March 2007AGI, Memphis, 1-2 March 2007
Roadmaps: Roadmaps: •A Ten Year Roadmap to Machines with Common Sense A Ten Year Roadmap to Machines with Common Sense (Push Singh, Marvin Minsky, 2002)(Push Singh, Marvin Minsky, 2002)•Euron (EU Robotics) Research Roadmap (2004)Euron (EU Robotics) Research Roadmap (2004)•Neuro-IT Roadmap (EU, A. Knoll, M de Kamps, 2006)Neuro-IT Roadmap (EU, A. Knoll, M de Kamps, 2006)
Challanges: Word games of increasing complexity: Challanges: Word games of increasing complexity: •20Q is the simplest, only object description.20Q is the simplest, only object description.•Yes/No game to understand situation.Yes/No game to understand situation.•Logical entailment competitions.Logical entailment competitions.
Collaborative project: concept description, Wordnet Collaborative project: concept description, Wordnet editoreditor
Steps Toward an AGI RoadmapSteps Toward an AGI RoadmapSteps Toward an AGI RoadmapSteps Toward an AGI Roadmap
AGI, Memphis, 1-2 March 2007AGI, Memphis, 1-2 March 2007
A Ten Year Roadmap to Machines with Common Sense A Ten Year Roadmap to Machines with Common Sense (Push Singh, Marvin Minsky, 2002)(Push Singh, Marvin Minsky, 2002)Large society of agents – is collaborative project Large society of agents – is collaborative project possible?possible?In Second Life?In Second Life?
Progress evaluationProgress evaluation• How to measure progress? Depends on the area.
• Variants of Turing test, Loebner competition, 20Q and other word games – methodology exists.
• Machine Intelligence Quotient (MIQ) can be systematically measured in human-machine cooperative control tasks, ex. using Intelligence Task Graph (ITG) as a modeling and analysis tool (Park, Kim, Lim 2001).
• HCI indicators of efficiency of various AI tools, ex. tutoring tools.
• Agent-Based Modeling and Behavior Representation (AMBR) Model Comparison (2005), compared humans/CA performance in a simplified air traffic controller environment.
• 2007 AAAI Workshop “Evaluating Architectures for Intelligence” proposed several ideas: in-city driving environment as a testbed for evaluating cognitive architectures, measuring incrementality and adaptivity components of general intelligent behavior.
Cognitive ageCognitive age• “Cognitive age” based on a set of problems that children
at a given age are able to solve, in several groups: e.g. vision and auditory perception, understanding language, common-sense reasoning, abstract reasoning, probing general knowledge about the world, learning, problem solving, imagination, creativity.
• Solving all problems from a given age group will qualify cognitive system to pass to the next grade.
• Some systems will show advanced age in selected areas, and not in the others – CA are very young in vision but quite advanced in mathematical reasoning, at least comparing to typical population.
• General world knowledge may be probed using a Q/A system. Compare CA answers with answers of a 5-year old child.
• Common sense knowledge bases are quite limited, except for CyC, but it seems to be quite difficult to use. Common-sense ontologies are missing, representation of concepts in dictionaries is minimal.
Humanized interface
Store
Applications, eg. 20 questions game
Query
Semantic memory
Parser
Part of speech tagger& phrase extractor
On line dictionariesActive search and dialogues with usersManual
verification
Realistic goals?Realistic goals?Different applications may require different knowledge representation.Start from the simplest knowledge representation for semantic memory. Find where such representation is sufficient, understand limitations. Drawing on such semantic memory an avatar may formulate and may answer many questions that would require exponentially large number of templates in AIML or other such language.
Adding intelligence to avatars involves two major tasks:
• building semantic memory model; • provide interface for natural communication.
Goal: create 3D human head model, with speech synthesis & recognition, use it to interact with Web pages & local programs: a Humanized InTerface (HIT).
Control HIT actions using the knowledge from its semantic memory.
Word gamesWord gamesWord gamesWord gamesWord games were popular before computer games. They are essential to the development of analytical thinking. Until recently computers could not play such games.
The 20 question game may be the next great challenge for AI, because it is more realistic than the unrestricted Turing test; a World Championship could involve human and software players.
Finding most informative questions requires knowledge and creativity.
Performance of various models of semantic memory and episodic memory may be tested in this game in a realistic, difficult application.
Asking questions to understand precisely what the user has in mind is critical for search engines and many other applications.
Creating large-scale semantic memory is a great challenge: ontologies, dictionaries (Wordnet), encyclopedias, MindNet (Microsoft), collaborative projects like Concept Net (MIT) …
HIT – larger view … HIT – larger view … HIT – larger view … HIT – larger view …
HIT projectsHIT projects
T-T-S synthesisT-T-S synthesis
Speech recognitionSpeech recognition
Talking headsTalking heads
BehavioralBehavioralmodelsmodels
GraphicsGraphics
Cognitive ArchitecturesCognitive Architectures
Cognitive Cognitive sciencescience
AIAI
A-MindsA-MindsLingu-botsLingu-bots
KnowledgeKnowledgemodelingmodelingInfo-retrievalInfo-retrieval
VR avatarsVR avatars
RoboticsRobotics
Brain modelsBrain models
Affective Affective computingcomputing
EpisodicEpisodicMemoryMemorySemantic Semantic
memorymemory
WorkingWorkingMemoryMemory
LearningLearning
DREAM architecture DREAM architecture
Natural input
modules Cognitive functions
Affectivefunctions
Web/text/databases interface
Behavior control
Control of devices
Talking head
Text to speechNLP
functions
Specializedagents
DREAM is concentrated on the cognitive functions + real time control, we plan to adopt software from the HIT project for perception, NLP, and other functions.