Research interests

Dr. Wilkins is a Senior Computer Scientist at the SRI International Artificial Intelligence Center, where he has been since receiving his Ph.D. from Stanford University in 1979. He has been principal investigator on numerous projects in planning, execution monitoring, and multiagent problem solving, and was elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 1998. He developed a planning and decision aid for Army small unit operations for the DARPA SUO Program and was a design team member for the FCS C4ISR architecture in FCS Phase 1, being responsible for Planning and Decision Aid design. He is currently managing projects on UAV airspace control and on a Cognitive Radio Policy Language.

He has published numerous journal articles and his 1988 book, Practical Planning: Extending the Classical AI Planning Paradigm, helped define the planning field and hierarchical planning techniques. He was the principal scientist for the final integrated demonstration for the DARPA/Rome Laboratory Planning Initiative (ARPI).

He has been a Visiting Scholar at both Stanford University and the University of Melbourne, and was instrumental in establishing the Australian Artificial Intelligence Institute. Mr. Wilkins was President of the Stanford Golf Club in 2005, and on the Board of Directors 2001-2006.

Past Projects

	Automating Exception Handing with Dynamic, Collaborative Scheduling This project will integrate flight scheduling, execution management, and distributed coordination capabilities to provide an integrated basis for generating and updating flight schedules in response to new requirements, negotiating adjustments to resource assignments, immediately detecting schedule deviations during execution and alerting users about them, and dynamically reoptimizing flight schedules. Joint work with Carnegie Mellon University on problems at the Air Mobility Command.
	Coordinated Multi-Agent Team Reasoning and Incremental eXecution SRI and team members are working on developing systems that enable people working in teams to quickly and effectively manage change.
	Distributed Continual Planning and Execution for Autonomous Air Vehicles This goal of this project is to develop a new software capability for the reprogrammable, coordinated command and control of teams of autonomous unmanned combat air vehicles (UCAVs) and unmanned ground vehicles (UGVs).
	ENDSTATE The objectives of the ENDSTATE initiative aim to provide new and innovative tools to aid in understanding and exploiting the vulnerabilities created by increasingly interconnected and interdependent physical network infrastructures. The vision was to bring together different but consistent model structures and analysis technologies so as to provide an insight into the vulnerabilities of the infrastructure. The insight could be used to derive the appropriate course of action, given desired effect
	Future Force Warrior The FFW program is developing an individual warrior / small combat team system of systems to complement the Future Combat System (FCS) program to achieve Army transformation objectives.
	Integrated Battle Command Rolling Start DARPA’s Integrated Battle Command program (IBC) aims to support the commander’s intuition, judgment, and creativity using flexible, intelligent decision aids. Unlike some previous efforts, IBC will focus on interactive methods that enable humans to guide the search for solutions.
	Multiagent Planning Architecture MPA is an open planning architecture that facilitates incorporation of new plan-related technologies, capitalizing on the benefits of distributed computing for efficiency and robustness. MPA provides protocols to support the sharing of knowledge and capabilities among agents involved in cooperative problem solving. MPA has been demonstrated in the air campaign planning domain, and was used as the infrastructure for the flagship demonstration of the DARPA Planning Initiative.
	Planning and Decision Aids for Small Unit Operations We developed a planning and decision aid (PDA) for the DARPA Small Unit Operations (SUO) program, to show the feasibility of using advanced planning technologies in SUO. The PDA monitors the execution of machine-understandable plans, using events as they are realistically reported in the battlespace, and alerts the user when the situation requires his attention.
	UAV Airspace Management System The ISX/SRI/BRG team will develop a UAV Airspace Management System (UAMS) that operates at a Battalion echelon level to deconflict multiple small UAV path plans in real time using limited sensors, communications, and processing resources. UAMS will employ a hybrid centralized/distributed architecture supporting dynamic coordination mode selection for each (group) of UAVs. This work is sponsored by the Army Aviation Applied Technology Directorate (AATD).
	XG Policy Control The vision of radically increased spectrum usage through XG-enabled radios requires regulatory bodies and spectrum holders to be convinced that the radios will follow rules and policies. This project will develop an expressive and extensible policy language with executable semantics, for describing policies that meet the needs of a wide variety of spectrum regulation bodies. We will also develop efficient reasoning algorithms to reason about policy compliance during radio operation.
	XG Spectrum Manager The XG Spectrum Manager is a set of applications software for managing networks of Software Defined Radios (SDRs) XG is DARPA ATO Program, and SRI is part of the team primed by the Shared Spectrum Company. SRI will assist in representing spectrum-use policies in a formal language, and develop algorithms for detecting transmitters.

Publications

The following are in reverse chronological order of publication.
Showing most recent 5 out of 57 [View All]

• Denker, G. and Elenius, D. and Wilkins D. Cognitive Radio Policy Language and Policy Engine . Cognitive Radio Technology, pp. 557-592, 2009.  [Details]

• Wilkins, D. and Smith, S. and Kramer, L. and Lee, T. and Rauenbusch, T. Airlift mission monitoring and dynamic rescheduling. Engineering Applications of Artificial Intelligence, vol. 21, no. 4, pp. 141-155, March 2008.  [Details]

• Wilkins D. and Denker, G. and Stehr, M.O. and Elenius, D. and Senanayake, R. and Talcott, C. Policy-Based Cognitive Radios. IEEE Wireless Communications, Special Issue on Cognitive Wireless Networks, vol. 14, no. 4, pp. 41-46, August 2007.  [Details]

• Denker, G. and Elenius, D. and Senanayake, R. and Stehr, M.O. and Wilkins, D. A Policy Engine For Spectrum Sharing, in New Frontiers in Dynamic Spectrum Access Networks, IEEE, pp. 55-65, April 2007.  [Details]

• Wilkins, D. and Smith, S. and Kramer, L. and Lee, T. and Rauenbusch, T. Execution Monitoring and Replanning with Incremental and Collaborative Scheduling, in ICAPS 2005 Workshop on Multiagent Planning and Scheduling, Monterey, CA, 2005.  [Details]