2018 - AAAI Robert S. Engelmore Memorial Lecture Award For sustained research excellence in constraint-based planning and scheduling technologies, deployment of those technologies to a range of significant real-world problems, and extensive service to the AI community that includes significant outreach to related technical fields.
2007 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to heuristic and mixed-initiative scheduling, constraint-based search, and the development of scalable AI systems.
His main research concerns Schedule, Mathematical optimization, Scheduling, Scheduling and Artificial intelligence. Stephen F. Smith combines subjects such as Solver, Unexpected events, Job shop scheduling and Operations research with his study of Schedule. His Mathematical optimization study integrates concerns from other disciplines, such as Theoretical computer science and Constraint satisfaction problem.
Stephen F. Smith works in the field of Scheduling, focusing on Dynamic priority scheduling in particular. His Scheduling research includes themes of Real-time computing, Two-level scheduling and Knowledge-based systems. He has included themes like Factory, Machine learning and Task, Task analysis in his Artificial intelligence study.
Stephen F. Smith mainly investigates Scheduling, Mathematical optimization, Schedule, Real-time computing and Job shop scheduling. His Scheduling research incorporates elements of Distributed computing, Artificial intelligence and Operations research. His work deals with themes such as Constraint satisfaction, Flow shop scheduling and Fair-share scheduling, which intersect with Mathematical optimization.
His Schedule study incorporates themes from Scheduling and Robustness. Stephen F. Smith interconnects Manufacturing engineering, Software engineering and Systems engineering in the investigation of issues within Scheduling. His biological study deals with issues like Control, which deal with fields such as Signal and Dedicated short-range communications.
His primary scientific interests are in Real-time computing, Control, Scheduling, Mathematical optimization and Scalability. His Real-time computing research incorporates themes from Transit, SIGNAL, Adaptive control and Job shop scheduling. Stephen F. Smith usually deals with Control and limits it to topics linked to Operations research and Bidding and Traffic engineering.
His work carried out in the field of Scheduling brings together such families of science as Robot, Traffic signal and Traffic flow. He works in the field of Mathematical optimization, namely Heuristics. His research in Asynchronous communication intersects with topics in Information exchange and Schedule.
His scientific interests lie mostly in Real-time computing, Intersection, Scalability, Value and Energy storage. His Real-time computing research is multidisciplinary, relying on both Transit bus, Robot, SIGNAL and Job shop scheduling. His Job shop scheduling study contributes to a more complete understanding of Scheduling.
Stephen F. Smith has included themes like Urban road and Inefficiency in his Scheduling study. His studies in Intersection integrate themes in fields like Quality of service, Bidding, Control theory, Control and Operations research. The Scalability study combines topics in areas such as Distributed computing and Asynchronous communication.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Modeling Supply Chain Dynamics: A Multiagent Approach
Jayashankar M. Swaminathan;Stephen F. Smith;Norman M. Sadeh.
Decision Sciences (1998)
ISIS—a knowledge‐based system for factory scheduling
Mark S. Fox;Stephen F. Smith.
Expert Systems (1984)
A learning system based on genetic adaptive algorithms
Stephen Frederick Smith.
Ph. D. Thesis, University of Pittsburgh (1980)
Flexible learning of problem solving heuristics through adaptive search
Stephen F. Smith.
international joint conference on artificial intelligence (1983)
A Constraint-Based Method for Project Scheduling with Time Windows
Amedeo Cesta;Angelo Oddi;Stephen F. Smith.
Journal of Heuristics (2002)
Cardiac troponin T composition in normal and regenerating human skeletal muscle.
Geza S. Bodor;Libby Survant;Ellen M. Voss;Stephen Smith.
Clinical Chemistry (1997)
Construction and maintaining detailed production plans: Investigations into the development of knowledge-based factory scheduling systems
Stephen F Smith;Mark S Fox;Peng Si Ow.
Ai Magazine (1986)
Using genetic algorithms to schedule flow shop releases
Gary A. Cleveland;Stephen F. Smith.
international conference on genetic algorithms (1989)
Slack-based heuristics for constraint satisfaction scheduling
Stephen F. Smith;Cheng-Chung Cheng.
national conference on artificial intelligence (1993)
Competition-Based Induction of Decision Models from Examples
David Perry Greene;Stephen F. Smith.
Machine Learning (1993)
Profile was last updated on December 6th, 2021.
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