33498	Learning from Multiple Sources of Inaccurate Data
33512	Strong Separation of Learning Classes
39179	Approximate Inference and Scientific Method
39193	Non U-Shaped Vacillatory and Team Learning
39201	Synthesizing Learners Tolerating Computable Noisy Data
39203	Predictive Learning Models for Concept Drift
39205	Learning a Subclass of Regular Patterns in Polynomial Time
39213	Anomalous Learning Helps Succinctness (Extended Abstract)
39215	Machine Induction Without Revolutionary Paradigm Shifts
39217	Vacillatory and BC Learning on Noisy Data
39219	Synthesizing Noise-Tolerant Language Learners
39369	Program Synthesis in the Presence of Infinite Number of Inaccuracies
39370	Learning with Refutation
39371	Learning Languages from Positive Data and Negative Counterexamples
39372	Learning Multiple Languages in Groups
39373	Learning and Extending Sublanguages
39374	Iterative Learning from Positive Data and Negative Counterexamples
39375	On Learning and Co-learning of Minimal Programs
39376	Learning Recursive Functions Refutably
39377	Learning of R.E. Languages from Good Examples
39378	Gold-Style and Query Learning Under Various Constraints on the Target Class
39379	Towards a Better Understanding of Incremental Learning
39380	Classes with Easily Learnable Subclasses
39381	Absolute Versus Probabilistic Classification in a Logical Setting
39382	Learning Languages in a Union
39383	Learning by Switching Type of Information
39384	Learning How to Separate
39385	Prudence in Vacillatory Language Identification (Extended Abstract)
39386	On Aggregating Teams of Learning Machines
39387	On Monotonic Strategies for Learning r.e. Languages
39388	Editors' Introduction
39666	One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples
39667	Learning in Friedberg Numberings
39683	Prescribed Learning of R.E. Classes
39703	Iterative Learning of Simple External Contextual Languages
39713	Numberings Optimal for Learning
94962	Input-Dependence in Function-Learning
108618	Synthesizing Enumeration Techniques for Language Learning
108778	Memory-Limited U-Shaped Learning
108779	Variations on U-Shaped Learning
108781	Generality's Price: Inescapable Deficiencies in Machine-Learned Programs
108782	On Learning to Coordinate: Random Bits Help, Insightful Normal Forms, and Competency Isomorphisms
108783	Robust Learning Aided by Context
108784	On Learning Limiting Programs
108785	Robust Learning - Rich and Poor
108909	Learning in the Presence of Inaccurate Information
109004	Intrinsic Complexity of Learning Geometrical Concepts from Positive Data
109005	On Learning Languages from Positive Data and a Limited Number of Short Counterexamples
109006	Language Learning From Texts: Degrees of Instrinsic Complexity and Their Characterizations
109007	Learning All Subfunctions of a Function
109008	Finite Learning by a ``Team'
109009	Probability is More Powerful Than Team for Language Identification from Positive Data
109010	On the Intrinsic Complexity of Language Identification
109011	Elementary Formal Systems, Intrinsic Complexity, and Procrastination
109012	On a Generalized Notion of Mistake Bounds
109013	Convergence to Nearly Minimal Size Grammars by Vacillating Learning Machines
109014	On the Power of Learning Robustly
109382	Mitotic Classes
109403	Learning Correction Grammars
192564	Ordinal Mind Change Complexity of Language Identification
192590	Control Structures in Hypothesis Spaces: The Influence on Learning
192598	Kolmogorov numberings and minimal identification
192612	The structure of intrinsic complexity of learning
192613	Mind Change Complexity of Learning Logic Programs
219437	Complexity Issues for Vacillatory Function Identification
219632	On the Limitations of Locally Robust Positive Reductions
219664	Branch and Bound on the Network Model
219666	Learning Languages from Positive Data and a Finite Number of Queries
235368	Not-So-Nearly-Minimal-Size Program Inference
235377	On Identification by Teams and Probabilistic Machines
268324	Language Learning by a 'Team' (Extended Abstract)
311057	Identifying Clusters from Positive Data
343558	Crowd Control: Coordinating Processes in Parallel
483927	Machine Learning of Higher Order Programs
484009	Banishing Robust Turing Completeness
526454	Performance Prediction Tools for Parallel Discrete-Event Simulation
526477	Load balancing for conservative simulation on shared memory multiprocessor systems
529009	Topology Independent Models for Parallel Computation
551516	Team Learning of Recursive Languages
619840	Language Learning With Some Negative Information
620043	Costs of General Purpose Learning
625959	Invertible Classes
625961	Some Recent Results in U-Shaped Learning
626800	Hypothesis Formation and Language Acquisition with an Infinitely-Often Correct Teacher
667715	Supply chain opportunities: panel session: opportunities for simulation in supply chain management
668672	Manufacturing sypply chain management: distributed supply chain simulation across enterprise boundaries
669170	Supply Chain Management Tradeoffs Analysis
669172	Simulation in the next millennium
669173	Expert simulation for on-line scheduling
669174	Experiences with Backward Simulation Based Approach for Lot Release Planning
669175	Manufacturing supply chain applications: modeling computer assembly operations for supply chain integration
669176	Analyzing the supply chain for a large logistics operation using simulation
669177	Stress testing a supply chain using simulation
669178	Criticality of detailed modeling in semiconductor supply chain simulation
669179	Simulation for emergency response: a framework for modeling and simulation for emergency response
669180	Integrated simulation and gaming architecture for incident management training
669181	Supply chain applications II: development of a high-level supply chain simulation model
669652	Implementations of Dispatch Rules in Parallel Manufacturing Simulation
671703	A concept prototype for integrated gaming and simulation for incident management
671980	Distributed simulation for interoperability testing along the supply chain
672152	Tradeoffs in building a generic supply chain simulation capability
718831	A simulation architecture for manufacturing interoperability testing
718898	Towards standards for integrated gaming and simulation for incident management
722687	Hypothesis Spaces for Learning
751716	Generalization and Specialization Strategies for Learning r.e. Languages
753821	Extremes in the Degrees of Inferability
753993	Characterizing Language Identification in Terms of Computable Numberings
754513	Generality's price: Inescapable deficiencies in machine-learned programs
768999	Low degree metabolites explain essential reactions and enhance modularity in biological networks
773097	Expert Simulation for On-Line Scheduling
861433	A Polynomial Time Learner for a Subclass of Regular Patterns
861453	Identifying Clusters from Positive Data
881953	The Intrinsic Complexity of Learning: A Survey
882968	Prescribed Learning of Indexed Families
887112	The Synthesis of Language Learners
887399	Incremental Concept Learning for Bounded Data Mining
887405	Complexity Issues for Vacillatory Function Identification
887407	Machine Induction Without Revolutionary Changes in Hypothesis Size
887908	Approximate Inference and Scientific Method
888352	Robust Behaviorally Correct Learning
888353	Learning languages from positive data and a finite number of queries
888354	On the intrinsic complexity of learning recursive functions
888355	Learning all subfunctions of a function
888356	Classes with easily learnable subclasses
888357	Learning by switching type of information
888358	Learning in the Presence of Partial Explanations
888359	Learning with the Knowledge of an Upper Bound on Program Size
888360	Computational Limits on Team Identification of Languages
888361	Elementary Formal Dystems, Intrinsic Complexity, and Procrastination
888362	Counting extensional differences in BC-learning
888363	Finite Identification of Functions by Teams with Success Ratio 1\over2 and Above
889905	Variations on U-shaped learning
889986	Learning in Friedberg numberings
890008	Results on memory-limited U-shaped learning
890011	Some natural conditions on incremental learning
890012	Iterative learning from positive data and negative counterexamples
908962	On Learning Limiting Programs
909135	On the Limitations of Locally Robust Positive Reductions
909146	Banishing Robust Turing Completeness
909211	An Infinite Class of Functions Identifiable Using Minimal Programs in all Kolmogorov Numberings
909212	Minimal Concept Identification and Reliability
931927	On a Question About Learning Nearly Minimal Programs
931928	On a Question of Nearly Minimal Identification of Functions
931929	On the Non-Existence of Maximal Inference Degrees for Language Identification
935214	On some open problems in reflective inductive inference
970373	Analytic evaluation of the expectation and variance of different performance measures of a schedule on a single machine under processing time variability
971443	Language Learning with Some Negative Information
971658	Synthesizing Learners Tolerating Computable Noisy Data
971659	On learning to coordinate: random bits help, insightful normal forms, and competency isomorphisms
971660	Robust Learning Aided by Context
971661	Vacillatory Learning of Nearly Minimal Size Grammars
971662	Robust learning--rich and poor
971971	Open Problems in 'Systems That Learn
972297	Program Synthesis in the Presence of Infinite Number of Inaccuracies
972299	Learning with Refutation
972301	Intrinsic complexity of learning geometrical concepts from positive data
972303	Language Learning from Texts: Degrees of Intrinsic Complexity and Their Characterizations
972305	Characterizing Language Identification by Standardizing Operations
972307	The Intrinsic Complexity of Language Identification
972309	Robust Learning Is Rich
973188	Learning languages in a union
973255	Non-U-shaped vacillatory and team learning
973327	Learning languages from positive data and negative counterexamples
980352	Strong separation of learning classes
980388	On an open problem in classification of languages
980390	Strong monotonic and set-driven inductive inference
998211	Machine Learning of Higher-Order Programs
999575	Some Independence Results for Control Structures in Complete Numberings
999577	The Structure of Intrinsic Complexity of Learning
1015648	Team Learning of Computable Languages
1015649	Prudence in Vacillatory Language Identification
1058514	Learning from Multiple Sources of Inaccurate Data
1058793	Identifying Clusters from Positive Data
1060860	Mitotic Classes in Inductive Inference
1088841	Ordinal Mind Change Complexity of Language Identification
1088921	Preface
1089922	Costs of general purpose learning
1089923	Predictive learning models for concept drift
1089924	Vacillatory and BC learning on noisy data
1089925	Synthesizing noise-tolerant language learners
1089926	Control structures in hypothesis spaces: the influence on learning
1089927	Anomalous Learning Helps Succinctness
1091264	Kolmogorov Numberings and Minimal Identification
1091310	Learning in the Presence of Inaccurate Information
1092297	Branch and bound on the network model
1092298	Learning languages and functions by erasing
1092299	On learning of functions refutably
1092300	On the learnability of recursively enumerable languages from good examples
1092301	Mind change complexity of learning logic programs
1092302	Learning how to separate
1092303	Program Size Restrictions in Computational Learning
1092304	On Aggregating Teams of Learning Machines
1095557	Learning a subclass of regular patterns in polynomial time
1095815	Invertible classes
1095864	Learning multiple languages in groups
1095877	A general comparison of language learning from examples and from queries
1095922	Learning languages from positive data and a limited number of short counterexamples
1096072	Learning and extending sublanguages
1096079	Absolute versus probabilistic classification in a logical setting
1096552	Prescribed learning of r.e. classes
1227594	One-shot learners using negative counterexamples and nearest positive examples
1237536	Uncountable Automatic Classes and Learning
1237540	Iterative Learning from Texts and Counterexamples Using Additional Information
1237546	Learning from Streams
1239195	Index Sets and Universal Numberings
1276130	On some open problems in monotonic and conservative learning
1280724	Components of an Incident Management Simulation and Gaming Framework and Related Developments
1340782	Input-Dependence in Function-Learning.
1347884	Joint Bidding in the Name-Your-Own-Price Channel: A Strategic Analysis.
1397352	Elementary formal systems, intrinsic complexity, and procrastination
1550187	Evolutionary games with two timescales
1560270	David vs. Goliath: An Analysis of Asymmetric Mixed-Strategy Games and Experimental Evidence
1565714	Pricing of Information Products on Online Servers: Issues, Models, and Analysis
1596224	Prescribed Learning of R.E. Classes
1661807	Learning in the presence of additional information and inaccurate information
1711503	Finite identification of functions by teams with success ratio 1/2 and above
1719033	Using simulation generators for modeling flexible manufacturing systems
