Index Catalog // ScholarsArchive@OSU

Learning in Complex Domains : Leveraging Multiple Rewards through Alignment

Creator:: Klinkhammer, Eric R.
Abstract:: In this thesis, we introduce alignment-based algorithms for improving the performance of reinforcement learning solutions for problems where the reward signal cannot be collapsed into a single number. Many real world problems require an agent to balance performance, longevity, and safety, and do so across different timelines. The key to...
Resource Type:: Masters Thesis

Adaptive Multiagent Traffic Management for Autonomous Robotic Systems

Creator:: Rebhuhn, Carrie
Abstract:: There is growing commercial interest in the use of unmanned aerial vehicles (UAVs) in urban environments, specifically for package delivery applications. However, the size, complexity and sheer numbers of expected UAVs makes conventional air traffic management that relies on human air traffic controllers infeasible. To enable UAVs to safely and...
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

Multi-Objective Optimization in Multiagent Systems

Creator:: Yliniemi, Logan Michael
Abstract:: Cooperative multiagent systems are used as solution concepts in many application domains including air traffic control, satellite communications, and extra planetary exploration. As systems become more distributed and complex, we observe three phenomena. First, these systems cannot be accurately modeled, rendering traditional model based control methods inadequate. Second, system parameters...
Resource Type:: Dissertation

Learning-based Control of Experimental Hybrid Fuel Cell Power Plant

Creator:: Gabler, Andrew
Abstract:: Direct red Solid Oxide Fuel Cell (SOFC) Turbine hybrid plants have the potential to dramatically increase power plant efficiency, decrease emissions, and provide fast response to transient loads. The US Department of Energy's (DOE) Hybrid Performance Project is an experimental hybrid SOFC plant, built at the National Energy Technology Laboratory...
Resource Type:: Masters Thesis

Multiagent learning for locomotion and coordination in tensegrity robotics

Creator:: Iscen, Atil
Abstract:: Tensegrity structures are composed of pure compressional elements that are connected via a network of pure tensional elements. The concept of tensegrity promises numerous advantages to the field of robotics. Tensegrity robots are, however, notoriously difficult to control due to their oscillatory nature and nonlinear interaction between the components. Multiagent...
Resource Type:: Dissertation

Theoretical and implementation improvements for difference evaluation functions

Creator:: Colby, Mitchell Kataichi
Abstract:: Multiagent learning with cooperative coevolutionary algorithms is a critical area of research, and is relevant to many real-world applications including air traffic control, distributed sensor network control, and game-theoretic applications such as border patrol. A key difficulty in multiagent learning is the credit assignment problem, where the impact of each...
Resource Type:: Dissertation

CLEAN learning to improve coordination and scalability in multiagent systems

Creator:: HolmesParker, Chris
Abstract:: Recent advances in multiagent learning have led to exciting new capabilities spanning fields as diverse as planetary exploration, air traffic control, military reconnaissance, and airport security. Such algorithms provide a tangible benefit over traditional control algorithms in that they allow fast responses, adapt to dynamic environments, and generally scale well....
Resource Type:: Dissertation

A multiagent approach to identifying innovation in design components

Creator:: Rebhuhn, Carrie M.
Abstract:: Innovation is a key element for a product to achieve market success, but identifying it within product or even defining the term is a difficult task. Identifying innovation has been approached in many different ways. Experts in design engineering may identify innovative designs based on an analysis of a product's...
Resource Type:: Masters Thesis

A neuro-evolutionary multiagent approach to multi-linked inverted pendulum control

Creator:: Sills, Stephen
Abstract:: Recent work has shown humanoid robots with spinal columns, instead of rigid torsos, benefit from both better balance and an increased ability to absorb external impact. Similarly, snake robots have shown promise as a viable option for exploration in confined spaces with limited human access, such as during power plant...
Resource Type:: Masters Thesis

Coevolution and transfer learning in a point-to-point fleet coordination problem

Creator:: Yliniemi, Logan Michael
Abstract:: In this work we present a multiagent Fleet Coordination Problem (FCP). In this formulation, agents seek to minimize the fuel consumed to complete all deliveries while maintaining acceptable on-time delivery performance. Individual vehicles must both (i) bid on the rights to deliver a load of goods from origin to destination...
Resource Type:: Masters Thesis

Optimizing ballast design of wave energy converters using evolutionary algorithms

Creator:: Colby, Mitchell
Abstract:: Wave Energy Converters (WECs) promise to be a viable alternative to current electrical generation methods. However, these WECs must become more efficient before wide-scale industrial use can become cost-effective. The efficiency of a WEC is primarily dependent upon its geometry and ballast configuration which are both difficult to evaluate, due...
Resource Type:: Masters Thesis

Combining coordination mechanisms to improve performance in multi-robot teams

Creator:: Nasroullahi, Ehsan
Abstract:: Coordination is essential to achieving good performance in cooperative multiagent systems. To date, most work has focused on either implicit or explicit coordination mechanisms, while relatively little work has focused on the benefits of combining these two approaches. In this work we demonstrate that combining explicit and implicit mechanisms can...
Resource Type:: Masters Thesis

Learning-based control and coordination of autonomous UAVs

Creator:: Bell, Adam R.
Abstract:: Uninhabited aerial vehicles, also called UAVs are currently controller by a combination of a human pilot at a remote location, and autopilot systems similar to those found on commercial aircraft. As UAVs transition from remote piloting to fully autonomous operation, control laws must be developed for the tasks to be...
Resource Type:: Masters Thesis

Condensing observation of locale and agents : a state representation

Creator:: Valenti, Brett A
Abstract:: Computing agents require state information to make coherent and useful decisions. A state representation is a numerical translation of the environment and conditions that are pertinent factors in an agent's decision making. Although many representations, when paired with clever learning algorithms, are able to coordinate and capture prey in specific...
Resource Type:: Masters Thesis

ScholarsArchive@OSU

Learning in Complex Domains : Leveraging Multiple Rewards through Alignment

Adaptive Multiagent Traffic Management for Autonomous Robotic Systems

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

Multi-Objective Optimization in Multiagent Systems

Learning-based Control of Experimental Hybrid Fuel Cell Power Plant

Multiagent learning for locomotion and coordination in tensegrity robotics

Theoretical and implementation improvements for difference evaluation functions

CLEAN learning to improve coordination and scalability in multiagent systems

A multiagent approach to identifying innovation in design components

A neuro-evolutionary multiagent approach to multi-linked inverted pendulum control

Coevolution and transfer learning in a point-to-point fleet coordination problem

Optimizing ballast design of wave energy converters using evolutionary algorithms

Combining coordination mechanisms to improve performance in multi-robot teams

Learning-based control and coordination of autonomous UAVs

Condensing observation of locale and agents : a state representation

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