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Filtering by: Creator Reitz, Stuart R. Remove constraint Creator: Reitz, Stuart R. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Mental Models of Mere Mortals with Explanations of Reinforcement Learning

    Creator:
    Anderson, Andrew A.
    Abstract:
    How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
    Resource Type:
    Masters Thesis
    Full Text:
    vector ~R(s, a), which gives the reward for each type. The total scalar reward is the sum across types

  • Distributed OpenCL : a platform for distributed, heterogeneous computing for domain scientists

    Creator:
    Dillon, William H.
    Abstract:
    It is possible to purchase, for as little as $10,000, a cluster of computers with the capability to rival the supercomputers of only a few years ago. Now, users that have little to no experience developing distributed applications or managing a cluster are in a position to do so. To...
    Resource Type:
    Dissertation
    Full Text:
    of easy-to-use numerical modeling tools such as Matlab, R and Mathematica, it has become easier for

  • Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

    Creator:
    Wei, Qi
    Abstract:
    Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...
    Resource Type:
    Dissertation

  • On Avoiding Power-Seeking by Artificial Intelligence

    Creator:
    Turner, Alexander M.
    Abstract:
    We do not know how to align a very intelligent AI agent's behavior with human interests. I investigate whether—absent a full solution to this AI alignment problem—we can build smart {\ai} agents which have limited impact on the world, and which do not autonomously seek power. In this thesis, I...
    Resource Type:
    Dissertation
    Full Text:
    In this work, we consider a standard Markov decision process (mdp) ⟨S,A, T,R, γ⟩ with state space S

  • Multi-criteria average reward reinforcement learning

    Creator:
    Natarajan, Sriraam
    Abstract:
    Reinforcement learning (RL) is the study of systems that learn from interaction with their environment. The current framework of Reinforcement Learning is based on receiving scalar rewards, which the agent aims to maximize. But in many real world situations, tradeoffs must be made among multiple objectives. This necessitates the use...
    Resource Type:
    Masters Thesis
    Full Text:
    Learning - R Learning 12 2.6 Model Based Average Reward Reinforcement Learning H Learning 15 Chapter 3

  • Version Control Systems: An Information Foraging Perspective

    Creator:
    Srinivasa Ragavan, Sruti
    Abstract:
    Software history and version control systems (VCS) are an important source of information for developers. This entails the need for a principled understanding of developers’ information seeking in VCS, both for improving existing tools as well as understanding requirements for new tools. However, it is only recently that researchers have...
    Resource Type:
    Masters Thesis
    Full Text:
    es (n um be re d la be ls) , , c on ne ct ed b y lin ks (r ed a rr ow s

  • Causal Structure Learning from Experiments and Observations

    Creator:
    Sinha, Meghamala
    Abstract:
    In this research, we address the problem of learning a single causal network structure from multiple dataset generated from different experiments. The experiments can be observational or interventional. We assume that each dataset is generated by an unknown causal network altered under different experimental conditions (interventions, manipulation or perturbation). As...
    Resource Type:
    Masters Thesis
    Full Text:
    bnLearn R package [35]. 13 Chapter 5: Comparative Studies 5.1 Biological Signaling Network In this

  • Layered rendering model for human teeth

    Creator:
    Shetty, Sudarshanram
    Abstract:
    This study introduces a layered model for rendering human teeth. Human teeth exhibit complex light interaction due to their layered structure. While the lighting responses of teeth have been studied in the dental industry for the production of realistic looking dentures, to our knowledge this is the first study of...
    Resource Type:
    Masters Thesis
    Full Text:
    ] is φ(x)= Φ 4πD e−σtrr(x) r(x) where: Φ=power of point light source. σtr=Effective transport

  • Development of an Integrated Generator Power Take-of Strategy using Model Predictive Control (MPC) for Ocean Wave Energy Conversion

    Creator:
    Sundaram, Srinivasan Subhash
    Abstract:
    Model Predictive Control (MPC) has previously been investigated on ocean waveenergy converters (WEC) to improve the amount of power captured, while respectingthe system constraints. Previous research done in the same area, focused onbuilding a control scheme by using the knowledge of the past & current statesof the system and predicting...
    Resource Type:
    Masters Thesis
    Full Text:
    length n, the input vector u, is a column vector of length r. A is an nxn square matrix that represents

  • 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
    Full Text:
    current program location `′ is at choice (A′, a′). The last choice is (A, a) with reward r seen in