Index Catalog // ScholarsArchive@OSU

Simulator-Defined MDP Planning with Applications in Natural Resource Management

Creator:: Alkaee Taleghan, Majid
Abstract:: This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
Resource Type:: Dissertation

Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

Creator:: Raghavan, Aswin
Abstract:: Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
Resource Type:: Dissertation

D₊₊ : Structural Credit Assignment in Tightly Coupled Multiagent Domains

Creator:: Rahmattalabi, Aida
Abstract:: Autonomous multiagent teams can be used in complex exploration tasks to both expedite the exploration and improve the efficiency. However, use of multiagent systems presents additional challenges. Specifically, in domains where the agents' actions are tightly coupled, coordinating multiple agents to achieve cooperative behavior at the group level is difficult....
Resource Type:: Masters Thesis

Incorporating and Learning Behavior Constraints for Sequential Decision Making

Creator:: Pinto, Jervis
Abstract:: Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...
Resource Type:: Dissertation

New learning modes for sequential decision making

Creator:: Judah, Kshitij
Abstract:: This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
Resource Type:: Dissertation

Just do it : an analysis of cultural factors behind the growth of Nike, Inc.

Creator:: Chen, Roger L.
Abstract:: The success of NIKE, Inc. is deemed miracle by professionals on both Wall Street and Madison Avenue. Research done in the past tends to credit the growth of NIKE, Inc. to its marketing strategies. By placing the achievement of the company in the postmodern context, this study analyzes the cultural...
Resource Type:: Masters Thesis
Full Text:: IDENTITIES . . . 49 Is NIKE Male? The Michael Jordan Phenomenon 50 CHAPTER FIVE JUST BUY IT

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Creator:: Wilson, Aaron
Abstract:: How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...
Resource Type:: Dissertation

Learning from action not taken in multiagent systems

Creator:: Khani, Newsha
Abstract:: Coordination in large multiagent systems in order to achieve a system level goal is a critical challenge. Given the agents' intention to cooperate, there is no guarantee that the agent actions will lead to good system objective especially when the system becomes large. One of the primary difficulties in such...
Resource Type:: Masters Thesis

Activity recognition in desktop environments

Creator:: Shen, Jianqiang
Abstract:: Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
Resource Type:: Dissertation

Defining micro-habitat relationships for juvenile black rockfish, Sebastes melanops

Creator:: Mann, Marion E.
Abstract:: The functioning of marine habitats needs to be understood in the context of the ecological relationships and associations between organisms and the physical and biogenic environment they inhabit. Thus, it becomes important to explore and define habitat features which contribute to these relationships and which are important in the life...
Resource Type:: Masters Thesis

ScholarsArchive@OSU

Simulator-Defined MDP Planning with Applications in Natural Resource Management

Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

D₊₊ : Structural Credit Assignment in Tightly Coupled Multiagent Domains

Incorporating and Learning Behavior Constraints for Sequential Decision Making

New learning modes for sequential decision making

Just do it : an analysis of cultural factors behind the growth of Nike, Inc.

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Learning from action not taken in multiagent systems

Activity recognition in desktop environments

Defining micro-habitat relationships for juvenile black rockfish, Sebastes melanops

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