aaai 1992 论文列表Proceedings of the 10th National Conference on Artificial Intelligence, San Jose, CA, USA, July 12-16, 1992. |
Artificial Intelligence and Molecular Biology.
Reasoning as Remembering: The Theory and Practice of CBR.
What Your Computer Really Needs to Know, You Learned in Kindergarten.
Wafer Scale Integration for Massively Parallel Memory-Based Reasoning.
Building Large-Scale and Corporate-Wide Case-Based Systems: Integration of the Organizational and Machine Executable Algorithms.
Mega-Classification: Discovering Motifs in Massive Datastreams.
Learning 10, 000 Chunks: What's It Like Out There?
Reactive Navigation through Rough Terrain: Experimental Results.
Landmark-Based Robot Navigation.
Integrating Planning and Reacting in a Heterogeneous Asynchronous Architecture for Controlling Real-World Mobile Robots.
A Reactive Robot System for Find and Fetch Tasks in an Outdoor Environment.
The Complexity of Propositional Default Logics.
Forming Concepts for Fast Inference.
An Improved Incremental Algorithm for Generating Prime Implicates.
Recognition Algorithms for the Loom Classifier.
An Empirical Analysis of Terminological Representation Systems.
A Non-Well-Founded Approach to Terminological Cycles.
Computing Least Common Subsumers in Description Logics.
On the Computational Complexity of Temporal Projection and Plan Validation.
Algorithms and Complexity for Reasoning about Time.
Temporal Reasoning in Sequence Graphs.
Complexity Results for Serial Decomposability.
Automatic Abduction of Qualitative Models.
Learning Engineering Models with the Minimum Description Length Principle.
Automated Model Selection Using Context-Dependent Behaviors.
Causal Approximations.
On the Qualitative Structure of a Mechanical Assembly.
Towards a Qualitative Lagrangian Theory of Fluid Flow.
Self-Explanatory Simulations: Scaling Up to Large Models.
Qualitative Simulation Based on a Logical Formalism of Space and Time.
Model-Based Case Adaptation.
When Should a Cheetah Remind You of a Bat? Reminding in Case-Based Teaching.
Common Sense Retrieval.
Generating Dialectical Examples Automatically.
Combining Circumscription and Modal Logic.
A Belief-Function Logic.
Ideal Introspective Belief.
A Logic of Knowledge and Belief for Recursive Modeling: A Preliminary Report.
A Symbolic Generalization of Probability Theory.
Lexical Imprecision in Fuzzy Constraint Networks.
A Logic for Revision and Subjunctive Queries.
From Statistics to Beliefs.
Nonmonotonic Sorts for Feature Structures.
Concurrent Actions in the Situation Calculus.
Deriving Properties of Belief Update from Theories of Action.
Formalising Reasoning about Change: A Qualitative Reasoning Approach.
Reasoning MPE to Multiply Connected Belief Networks Using Message Passing.
Adaptive Model-Based Diagnostic Mechanism Using a Hierarchical Model Scheme.
Consistency-Based Diagnosis in Physiological Domains.
Dynamic MAP Calculations for Abduction.
An Average-Case Analysis of Branch-and-Bound with Applications: Summary of Results.
Performance of IDA on Trees and Graphs.
Linear-Space Best-First Search: Summary of Results.
Moving Target Search with Intelligence.
Modeling Accounting Systems to Support Multiple Tasks: A Progress Report.
Improved Decision-Making in Game Trees: Recovering from Pathology.
On Optimal Game Tree Propagation for Imperfect Players.
Real-time Metareasoning with Dynamic Trade-off Evaluation.
Comparison of Three Algorithms for Ensuring Serializable Executions in Parallel Production Systems.
Can Real-Time Search Algorithms Meet Deadlines?
Run-Time Prediction for Production Systems.
Using Deep Structure to Locate Hard Problems.
How Long Will It Take?
Hard and Easy Distributions of SAT Problems.
Solving Constraint Satisfaction Problems Using Finite State Automata.
On the Minimality and Decomposability of Constraint Networks.
A New Method for Solving Hard Satisfiability Problems.
An Improved Connectionist Activation Function for Energy Minimization.
On the Density of Solutions in Equilibrium Points for the Queens Problem.
An Efficient Cross Product Representation of the Constraint Satisfaction Problem Search Space.
Semantic Evaluation as Constraint Network Consistency.
Efficient Propositional Constraint Propagation.
Learning from Goal Interactions in Planning: Goal Stack Analysis and Generalization.
Constrained Decision Revision.
Analyzing Failure Recovery to Improve Planner Design.
On the Complexity of Domain-Independent Planning.
Achieving the Functionality of Filter Conditions in a Partial Order Planner.
The Expected Value of Hierarchical Problem-Solving.
Cultural Support for Improvisation.
Grouping Iso-Velocity Points for Ego-Motion Recovery.
A Computational Model for Face Location Based on Cognitive Principles.
Computation of Upper-Bounds for Stochastic Context-Free Languages.
Shipping Departments vs. Shipping Pacemakers: Using Thematic Analysis to Improve Tagging Accuracy.
Classifying Texts Using Relevancy Signatures.
A Probabilistic Parser Applied to Software Testing Documents.
Parsing Run Amok: Relation-Driven Control for Text Analysis.
Literal Meaning and the Comprehension of Metaphors.
An On-Line Computational Model of Human Sentence Interpretation.
Actions, Beliefs and Intentions in Rationale Clauses and Means Clauses.
An Approach to the Representation of Iterative Situations.
A General-Equilibrium Approach to Distributed Transportation Planning.
On the Synthesis of Useful Social Laws for Artificial Agent Societies (Preliminary Report).
Using Joint Responsibility to Coordinate Collaborative Problem Solving in Dynamic Environments.
Constrained Intelligent Action: Planning Under the Influence of a Master Agent.
Inductive Policy.
Empirical Analysis of the General Utility Problem in Machine Learning.
A Statistical Approach to Solving the EBL Utility Problem.
COMPOSER: A Probabilistic Solution to the Utility Problem in Speed-Up Learning.
A Theory of Unsupervised Speedup Learning.
An Analysis of Bayesian Classifiers.
Oblivious PAC Learning of Concept Hierarchies.
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning.
Thomas L. Dean Dana Angluin Kenneth Basye Sean P. Engelson Leslie Pack Kaelbling Evangelos Kokkevis Oded Maron
Reinforcement Learning with a Hierarchy of Abstract Models.
Automatic Programming of Robots Using Genetic Programming.
Acquisition of Automatic Activity through Practice: Changes in Sensory Input.
Reinforcement Learning with Perceptual Aliasing: The Perceptual Distinctions Approach.
Using Symbolic Learning to Improve Knowledge-Based Neural Networks.
Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta.
Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding.
A Framework for Integrating Fault Diagnosis and Incremental Knowledge Acquisition in Connectionist Expert Systems.
Complementary Discrimination Learning with Decision Lists.
Sparse Data and the Effect of Overfitting Avoidance in Decision Tree Induction.
Classifier Learning from Noisy Data as Probabilistic Evidence Combination.
Discrete Sequence Prediction and its Applications.
The Feature Selection Problem: Traditional Methods and a New Algorithm.
ChiMerge: Discretization of Numeric Attributes.
Polynomial-Time Learning with Version Spaces.
COGIN: Symbolic Induction with Genetic Algorithms.
The Attribute Selection Problem in Decision Tree Generation.
A Personal Learning Apprentice.
Learning to Learn Decision Trees.
Learning in FOL with a Similarity Measure.
Operational Definition Refinement: A Discovery Process.
Discovery of Equations: Experimental Evaluation of Convergence.
Theory-Driven Discovery of Reaction Pathways in the MECHEM System.
Symmetry as Bias: Rediscovering Special Relativity.
Learning Relations by Pathfinding.
Discrimination-Based Constructive Induction of Logic Programs.
Learning to Disambiguate Relative Pronouns.
A Connectionist Parser with Recursive Sentence Structure and Lexical Disambiguation.
Steps from Explanation Planning to Model Construction Dialogues.
Results of Encoding Knowledge with Tutor Construction Tools.
Generating Cross-References for Multimedia Explanation.
Understanding Causal Descriptions of Physical Systems.