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Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning | Mastering the game of Go with deep neural networks and tree search | On Relevance, Probabilistic Indexing and Information Retrieval | eng_Latn | 20,100 |
to appear in the proceedings of the tenth conference on computer generated forces and behavioral representation 1 multi - tasking and cognitive workload in an act - r model of a simplified air traffic control task . | the psychology of human - computer interaction . | Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning | eng_Latn | 20,101 |
Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms | Learning to act using real-time dynamic programming | Full-System Simulation of big.LITTLE Multicore Architecture for Performance and Energy Exploration | eng_Latn | 20,102 |
Biologically Plausible Multi-Dimensional Reinforcement Learning in Neural Networks | Learning internal representations by error propagation | Playing Alone, Playing With Others: Differences in Player Experience and Indicators of Wellbeing | eng_Latn | 20,103 |
Global Continuous Optimization with Error Bound and Fast Convergence | Bandit-based planning and learning in continuous-action Markov decision processes | A Machine Learning-Based Design Representation Method for Designing Heterogeneous Microstructures | eng_Latn | 20,104 |
SimEd: Simulating Education as a Multi Agent System | Minimal-Intelligence Agents for Bargaining Behaviors in Market-Based Environments | Towards object mapping in non-stationary environments with mobile robots | eng_Latn | 20,105 |
Building Poker Agent Using Reinforcement Learning with Neural Networks | Neural Networks A Comprehensive Foundation | Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming | eng_Latn | 20,106 |
Deep Reinforcement Learning for Building HVAC Control | Energy efficient building climate control using Stochastic Model Predictive Control and weather predictions | An aperture antenna for bluetooth, WLAN, WiMax, ZigBee and LTE applications | eng_Latn | 20,107 |
Multi-agent Q-learning for autonomous D2D communication | Exploiting social ties for cooperative D2D communications: a mobile social networking case | GDNF: a glial cell line-derived neurotrophic factor for midbrain dopaminergic neurons. | eng_Latn | 20,108 |
Cognitive Decision Making Process Supervising the Radio Dynamic Reconfiguration | Reinforcement Learning: A Survey | Ethanol production from potato peel waste (PPW). | eng_Latn | 20,109 |
AIXIjs: A Software Demo for General Reinforcement Learning | Near-optimal regret bounds for reinforcement learning | pharmacological importance of clitoria ternatea – a review prof dr . | eng_Latn | 20,110 |
Payday loans and consumer financial health | Golden Eggs and Hyperbolic Discounting | Learning how to flock: deriving individual behaviour from collective behaviour with multi-agent reinforcement learning and natural evolution strategies | eng_Latn | 20,111 |
Multi-Agent Q-Learning for Minimizing Demand-Supply Power Deficit in Microgrids | Demand Side Management in Smart Grids | Stabilization of vehicle rollover by nonlinear model predictive control | eng_Latn | 20,112 |
Developing multi-agent systems with a FIPA-compliant agent framework | BDI Agents: From Theory to Practice | Interactions Among Working Memory, Reinforcement Learning, and Effort in Value-Based Choice: A New Paradigm and Selective Deficits in Schizophrenia | eng_Latn | 20,113 |
A context-based theory of recency and contiguity in free recall | The Mind and Brain of Short-Term Memory | Asynchronous Advantage Actor-Critic Agent for Starcraft II | eng_Latn | 20,114 |
Knowledge Management and Problem Solving in Real Time: The Role of Swarm Intelligence | Convergent and discriminant validation by the multitrait-multimethod matrix. | Automated Accident Alert | eng_Latn | 20,115 |
agent samples network topology agent learns from memory . | Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching | Ground Moving Targets Imaging Algorithm for Synthetic Aperture Radar | eng_Latn | 20,116 |
Multi-agent quadrotor testbed control design: integral sliding mode vs. reinforcement learning | Reinforcement Learning: An Introduction | Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming | eng_Latn | 20,117 |
Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games | game theory - based opponent modeling in large imperfect - information games . | Artificial intelligence: A modern approach | kor_Hang | 20,118 |
Coordinating multi-agent reinforcement learning with limited communication | Coordinated Reinforcement Learning | Automatic optic disc segmentation with peripapillary atrophy elimination | eng_Latn | 20,119 |
Hierarchical Multi-Agent Reinforcement Learning through Communicative Actions for Human-Robot Collaboration | Human-Robot Collaboration: A Survey | Statistics of Speckle in Ultrasound B-Scans | eng_Latn | 20,120 |
Differential reward magnitude and human conditioning with social reinforcers | In two separate investigations, human Ss received social stimuli as reinforcers in a discrete-trials paradigm of instrumental conditioning. The major variable of interest was reward magnitude utilizing stimuli from attraction research. In the first experiment, a group receiving large reward performed the instrumental response faster than a group receiving small reward. In a second experiment, two groups received large and small reward, respectively, and a third group received differential magnitudes of reward (both large and small) correlated with external stimuli. The results indicated that the differential group was depressed below both the large and small groups in the first portion of the response. These data (1) demonstrate magnitude of reward effects in an instrumental learning paradigm utilizing human Ss and (2) indicate that attraction stimuli function in an analogous manner to more traditional reinforcers. | We prove existence of solutions for a class of systems of subelliptic PDEs arising from Mean Field Game systems with H\"ormander diffusion. These results are motivated by the feedback synthesis Mean Field Game solutions and the Nash equilibria of a large class of $N$-player differential games. | eng_Latn | 20,121 |
The Great Fish War: A Cooperative Solution | The competitive al location of a common property resource is analyzed taking explicit account of the fact that the resource users must confront each other repeatedly. This means that future retaliation for noncooperatrve behavior is possible. The likelihood of enforcing cooperative behavior with the credible threat of retaliation is analyzed using the theory of repeated games. | ABSTRACT In this paper, we deal with lotteries to finance the preservation of the global commons and we carry out simulations on an agent-based artificial society model. Focusing on the preservation of the global commons, such as the atmospheric quality, we show that financing by means of lotteries with selective incentives is effective, as compared to voluntary contributions without those incentives, when the condition of the global commons does not become excessively worse. | eng_Latn | 20,122 |
.57 Experience-based Exploration of Complex Energy Systems | In our energy-restricted world, planners and engineers have to cope with problems of CO2 emissions and oil- and gas-shortages. Many planning activities not captured under the heading of “futures studies” share common goals like dealing with an uncertain, complex future. We focus on two novel approaches: agent-based modelling and serious games. These approaches, even though they stem from the same general systems theory roots, allow its users to experience “reality” in different ways. This has implications for when and how to use these methods in scanning future developments and how these are communicated. | Abstract : Experimentation Data Process: *Lockheed Martin experimentation at the Center for Innovation, -Constructive Simulations, -Human-in-the-Loop Simulation; *Two main issues; -Data Extraction/Storage, -Data Manipulation/Reduction; *Early Experimentation (2006 Processes), -Post Run extraction, -Manual reduction/consolidation; *Current Experimentation (2007 Processes), -Real-Time and Post Run extraction, -Hyperion Intelligence for Data reduction | eng_Latn | 20,123 |
Guaranteed Control Synthesis for Continuous Systems in Uppaal Tiga | We present a method for synthesising control strategies for continuous dynamical systems. We use Uppaal Tiga for the synthesis in combination with a set-based Euler method for guaranteeing that the synthesis is safe. We present both a general method and a method which provides tighter bounds for monotone systems. As a case-study, we synthesize a guaranteed safe strategy for a simplified adaptive cruise control application. We show that the guaranteed strategy is only slightly more conservative than the strategy generated in the original adaptive cruise control paper which uses a discrete non guaranteed strategy. Also, we show how reinforcement learning may be used to obtain optimal sub-strategies. | Abstract Making schedules for batch controlled plants in the chemical process industry is a topic often discussed. A wide range of scheduling tools have a separated model and a mathematical optimizer. In this paper we discuss a solution where a event discrete simulation tool is connected to the DCS. With all necessary model information stored in the DCS the scheduling tools in plant independent, where a optimizer (a combination of heuristics and genetic algorithms) generates a proposal for the final schedule. | eng_Latn | 20,124 |
Does Transit Mean Business? Reconciling Academic, Organizational, and Political Perspectives on Reforming Transit Fare Policies | Transit fares are typically of two sorts: flat or differentiated. Flexible, differentiated transit fares, which vary by mode, distance, and/or time-of-day to reflect differences in the marginal costs of service provision, can increase the efficiency, efficacy, and equity of transit service. Technological advancements, particularly with smart cards, have reduced administrative and operational barriers to flexible fares but few transit operating agencies have moved to adopting variable fares.Transit agencies tend to be reactive to budgetary pressures and reluctant to change fare structures when changing fare levels. While there is some interest in flexible fares, transit managers seek to avoid risk and do not want to draw unwanted publicity, making this more than a technical challenge. | TAC-02 was the third in a series of Trading Agent Competition events fostering research in automating trading strategies by showcasing alternate approaches in an open-invitation market game. TAC presents a challenging travel-shopping scenario where agents must satisfy client preferences for complementary and substitutable goods by interacting through a variety of market types. Michigan's entry, Walverine, attempts to bid optimally based on a competitive analysis of the TAC travel economy. Walverine's approach embodies several techniques not previously employed in TAC: (1) price prediction based on competitive equilibrium analysis, (2) hedged optimization with respect to a model of outlier prices, (3) optimal bidding based on a decision-theoretic calculation of bid actions, and (4) reinforcement learning for CDA trading strategies. Each of these is potentially applicable in a broad class of trading environments. | eng_Latn | 20,125 |
GA3C: GPU-based A3C for Deep Reinforcement Learning | Dueling Network Architectures for Deep Reinforcement Learning | statistical modeling of high - frequency financial data . | eng_Latn | 20,126 |
Computational Intelligence in Automotive Applications | Reinforcement Learning: An Introduction | A framework for intelligence analysis using spatio-temporal storytelling | eng_Latn | 20,127 |
Feature-based aggregation and deep reinforcement learning: a survey and some new implementations | Reinforcement Learning with Soft State Aggregation | Asynchronous Stochastic Approximation and Q-Learning | eng_Latn | 20,128 |
ACCNet: Actor-Coordinator-Critic Net for"Learning-to-Communicate"with Deep Multi-agent Reinforcement Learning | Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments | Activating mutations of the noonan syndrome-associated SHP2/PTPN11 gene in human solid tumors and adult acute myelogenous leukemia. | kor_Hang | 20,129 |
Shielded Decision-Making in MDPs. | Planning with Markov Decision Processes: An AI Perspective | introduction to a large - scale general purpose ground truth database : methodology , annotation tool and benchmarks . | eng_Latn | 20,130 |
Hierarchical Reinforcement Learning with Hindsight | Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning | Performance analysis of virtualized VPN endpoints | eng_Latn | 20,131 |
Effective Master-Slave Communication On A Multi-Agent Deep Reinforcement Learning System | Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games. | one introduction to social network analysis 1 . 2 concept of a social network 4 models for social networks with statistical applications figure 1 . 1 . | eng_Latn | 20,132 |
Evolving Agents for the Hanabi 2018 CIG Competition | Mastering the game of Go with deep neural networks and tree search | Cross-Graph Learning of Multi-Relational Associations | eng_Latn | 20,133 |
IRON: Functional Encryption using Intel SGX | Oblivious multi-party machine learning on trusted processors | Distributed Reinforcement Learning via Gossip | eng_Latn | 20,134 |
Blokus Duo game on FPGA | The History Heuristic and Alpha-Beta Search Enhancements in Practice | How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary? | kor_Hang | 20,135 |
A Multiworld Testing Decision Service | Agnostic Active Learning Without Constraints | Efficient Exploration in Reinforcement Learning with Hidden State | eng_Latn | 20,136 |
Efficient Reinforcement Learning Through Evolving Neural Network Topologies | BOXES: AN EXPERIMENT IN ADAPTIVE CONTROL | Information systems security design methods: implications for information systems development | eng_Latn | 20,137 |
Bootstrapped Thompson Sampling and Deep Exploration | r - max - a general polynomial time algorithm for near - optimal reinforcement learning . | Blockchain-based publicly verifiable data deletion scheme for cloud storage | eng_Latn | 20,138 |
Removal of Data Incest in Multi-agent Social Learning in Social Networks | Gossip Algorithms for Distributed Signal Processing | Adaptive game AI with dynamic scripting | eng_Latn | 20,139 |
A Lyapunov-based Approach to Safe Reinforcement Learning | Multi-Objective Deep Reinforcement Learning | Empirical evaluation methods for multiobjective reinforcement learning algorithms | eng_Latn | 20,140 |
Smart exploration in reinforcement learning using absolute temporal difference errors | On-Line Q-Learning Using Connectionist Systems | Traditional Anishinabe Healing in a Clinical Setting: The Development of an Aboriginal Interdisciplinary Approach to Community-based Aboriginal Mental Health Care | eng_Latn | 20,141 |
Dynamic Programming for Partially Observable Stochastic Games | Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes | The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems | eng_Latn | 20,142 |
Hierarchical Reinforcement Learning: A Survey | Reinforcement Learning, Conditioning, and the Brain: Successes and Challenges | A Comparison of Lasso-type Algorithms on Distributed Parallel Machine Learning Platforms | eng_Latn | 20,143 |
Offline and online time in Sequential Decision-Making Problems | Evolutionary optimization in uncertain environments-a survey | Reinforcement Learning: A Survey | eng_Latn | 20,144 |
Learning Policy Representations in Multiagent Systems | VAIN: Attentional Multi-agent Predictive Modeling | DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess | eng_Latn | 20,145 |
How impulsivity affects consumer decision-making in e-commerce | Task complexity and contingent processing in decision making: An information search and protocol analysis | AI Challenges in Human-Robot Cognitive Teaming | eng_Latn | 20,146 |
Hierarchical Deep Multiagent Reinforcement Learning | Human-level control through deep reinforcement learning | Blockchain-based mobile fingerprint verification and automatic log-in platform for future computing | eng_Latn | 20,147 |
Extending the Hierarchical Deep Reinforcement Learning framework | TensorFlow: A system for large-scale machine learning | Calibrated Fairness in Bandits | eng_Latn | 20,148 |
Multi-Agent Reinforcement Learning with Vicarious Rewards | Neuronlike adaptive elements that can solve difficult learning control problems | The urban forest in Beijing and its role in air pollution reduction | eng_Latn | 20,149 |
ALK : L EARNING TO W ALK IN G RAPH WITH M ONTE C ARLO T REE S EARCH | Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning | PRODIGY: an integrated architecture for planning and learning | yue_Hant | 20,150 |
Intelligent Agents on the Internet: Fact, Fiction, and Forecast | An Introduction to Least Commitment Planning | Explanation-based learning: a problem solving perspective | eng_Latn | 20,151 |
Online least-squares policy iteration for reinforcement learning control | temporal differences - based policy iteration and applications in neuro - dynamic programming . | Knowledge-based Sales Advisory: Experiences and Future Directions | eng_Latn | 20,152 |
Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games. | ImageNet Large Scale Visual Recognition Challenge | Reinforcement Learning: An Introduction | eng_Latn | 20,153 |
Recurrent Relational Networks | OptNet: Differentiable Optimization as a Layer in Neural Networks | Influences on cooperation in BitTorrent communities | eng_Latn | 20,154 |
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation | Utility functions in autonomic systems | Evaluating Automated Facial Age Estimation Techniques for Digital Forensics | eng_Latn | 20,155 |
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable | Bandit Based Monte-Carlo Planning | Exploration in model-based reinforcement learning by empirically estimating learning progress | eng_Latn | 20,156 |
Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations | Deep Recurrent Q-Learning for Partially Observable MDPs | a new species of glugea thelohan , 1891 in the red sea bream pagrus major ( temminck & schlegel ) ( teleostei : sparidae ) from china . | eng_Latn | 20,157 |
Portfolio Allocation for Bayesian Optimization | Gambling in a rigged casino: The adversarial multi-armed bandit problem | An Overview of Yoga Research for Health and Well-Being | eng_Latn | 20,158 |
Learning to Communicate and Act in Cooperative Multiagent Systems Using Hierarchical Reinforcement Learning | multi - agent reinforcement learning : independent versus cooperative agents . | postoperative elongation of the xiphoid process - - report of a case - - . | eng_Latn | 20,159 |
A novel multi-step reinforcement learning method for solving reward hacking | Distributed Prioritized Experience Replay | Dermatology on instagram. | eng_Latn | 20,160 |
Failure as a Service ( FaaS ) : A Cloud Service for Large-Scale , Online Failure Drills | Characterizing, modeling, and generating workload spikes for stateful services | Value-function reinforcement learning in Markov games | eng_Latn | 20,161 |
A gentle introduction to the universal algorithmic agent AIXI | Reinforcement Learning: An Introduction | Towards mechanisms for detection and prevention of data exfiltration by insiders: keynote talk paper | eng_Latn | 20,162 |
agent samples network topology agent learns from memory . | Reinforcement Learning: A Survey | alvinn : an autonomous land vehicle in a neural network . | eng_Latn | 20,163 |
exploration in gradient - based reinforcement learning . | Approximate Planning in Large POMDPs via Reusable Trajectories | A unified optimization framework for auction and guaranteed delivery in online advertising | eng_Latn | 20,164 |
parameter sharing reinforcement learning architecture for multi agent driving behaviors . | Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm | Factors affecting the adoption of e-books by information professionals: | eng_Latn | 20,165 |
Generalization in Reinforcement Learning: Safely Approximating the Value Function | Learning from delayed rewards | Reinforcement Learning And Its Application To Control | eng_Latn | 20,166 |
Monte-Carlo Tree Search for the Game of 7 Wonders | PROGRESSIVE STRATEGIES FOR MONTE-CARLO TREE SEARCH | Online monitoring and control of the biogas process | eng_Latn | 20,167 |
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning | The Arcade Learning Environment: An Evaluation Platform for General Agents | Study on GSP algorithm based on Hadoop | eng_Latn | 20,168 |
Robot Programming by Demonstration with Crowdsourced Action Fixes | Active learning literature survey | Caspase-3-dependent apoptosis in Escherichia coli-infected urothelium: involvement of inducible nitric oxide synthase | eng_Latn | 20,169 |
Approaching Bayes-optimalilty using Monte-Carlo tree search | Exploring compact reinforcement-learning representations with linear regression | Help Yourself : A Virtual Self-Assist Agent | eng_Latn | 20,170 |
Multi-source heterogeneous data fusion | Data quality: The other face of Big Data | An Information-Theoretic Optimality Principle for Deep Reinforcement Learning | eng_Latn | 20,171 |
The Anatomy of Motivation: An Evolutionary-Ecological Approach | Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models | A comparison of platforms for implementing and running very large scale machine learning algorithms | kor_Hang | 20,172 |
adversarially learned likelihood - ratio . | Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm | Biologically-Inspired Control for Self-Adaptive Multiagent Systems | eng_Latn | 20,173 |
Strategic Market Choice: Frequent Call Markets vs. Continuous Double Auctions for Fast and Slow Traders | Computerized and High-Frequency Trading | An Efficient Deep Reinforcement Learning Model for Urban Traffic Control | eng_Latn | 20,174 |
Autonomous HVAC Control , A Reinforcement Learning Approach | Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem | Markov Games as a Framework for Multi-Agent Reinforcement Learning | eng_Latn | 20,175 |
Hierarchical Multi-Agent Reinforcement Learning through Communicative Actions for Human-Robot Collaboration | Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition | Does food marketing need to make us fat? A review and solutions | eng_Latn | 20,176 |
A New Optimization Layer for Real-Time Bidding Advertising Campaigns | Real-Time Bidding by Reinforcement Learning in Display Advertising | chapter 13 : ethical decision making : where we ' ve been and where we ' re going . | eng_Latn | 20,177 |
A Comparison of Exploration/Exploitation Techniques for a Q-Learning Agent in the Wumpus World | Artificial intelligence: A modern approach | Trust Aware Recommender Systems : A Survey on Implicit Trust Generation Techniques | eng_Latn | 20,178 |
A Multiagent Approach to $Q$-Learning for Daily Stock Trading | Reinforcement Learning: An Introduction | Towards Modeling and Measuring Information Literacy in Secondary Education | kor_Hang | 20,179 |
Adversarial Reinforcement Learning in a Cyber Security Simulation | Game Theory with Learning for Cyber Security Monitoring | An overview of models of technological singularity | eng_Latn | 20,180 |
When Does Model-Based Control Pay Off? | Cognitive Control Predicts Use of Model-based Reinforcement Learning | Translocation of Bacillus thuringiensis in Phaseolus vulgaris tissues and vertical transmission in Arabidopsis thaliana | eng_Latn | 20,181 |
Potential-based difference rewards for multiagent reinforcement learning | A Comprehensive Survey of Multi-Agent Reinforcement Learning | An Autonomous Time-Dependent SLA Negotiation Strategy for Cloud Computing | eng_Latn | 20,182 |
A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools | Playing FPS Games with Deep Reinforcement Learning | Autoencoders, Minimum Description Length and Helmholtz Free Energy | yue_Hant | 20,183 |
An Analysis of Stochastic Game Theory for Multiagent Reinforcement Learning | Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm | General vestibular testing | kor_Hang | 20,184 |
a deep q - network for the beer game : a deep reinforcement learning algorithm to solve inventory optimization problems . | CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning | QELAR: A Machine-Learning-Based Adaptive Routing Protocol for Energy-Efficient and Lifetime-Extended Underwater Sensor Networks | eng_Latn | 20,185 |
A Survey of Exploration Strategies in Reinforcement Learning | Near-Optimal Reinforcement Learning in Polynomial Time | Detecting HTTP Botnet with Clustering Network Traffic | eng_Latn | 20,186 |
Interactive evolution for the procedural generation of tracks in a high-end racing game | Efficient Reinforcement Learning Through Evolving Neural Network Topologies | Teacher Concerns During Initial Implementation of a One-to-One Laptop Initiative at the Middle School Level | eng_Latn | 20,187 |
Is multiagent deep reinforcement learning the answer or the question? A brief survey | Mean Field Multi-Agent Reinforcement Learning | Learning from delayed rewards | eng_Latn | 20,188 |
Deep reinforcement learning for time series: playing idealized trading games | Hierarchical Multiscale Recurrent Neural Networks | Agent Based Framework for Scalability in Cloud Computing | eng_Latn | 20,189 |
Analysis and Optimization of Deep CounterfactualValue Networks | Efficient Nash Equilibrium Approximation through Monte Carlo Counterfactual Regret Minimization | Bayesian Poker | eng_Latn | 20,190 |
Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games | Deterministic Policy Gradient Algorithms | Bayes' Bluff: Opponent Modelling in Poker | eng_Latn | 20,191 |
Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction | Near-Optimal Reinforcement Learning in Polynomial Time | Modeling the Forest or Modeling the Trees A Comparison of System Dynamics and Agent-Based Simulation | eng_Latn | 20,192 |
Final report : Dynamic Asset Allocation Using Reinforcement Learning | DEEP REINFORCEMENT LEARNING IN PARAMETER- IZED ACTION SPACE | deception in cosmetics advertising : examining cosmetics advertising claims in fashion magazine ads 化 妆 品 广 告 中 的 欺 骗 : 分 析 时 尚 杂 志 广 告 中 的 化 妆 品 广 告 . | eng_Latn | 20,193 |
Hybrid Reward Architecture for Reinforcement Learning | An object-oriented representation for efficient reinforcement learning | Factors affecting utilization of postnatal care service in Jabitena district, Amhara region, Ethiopia | eng_Latn | 20,194 |
Interactive Narrative Personalization with Deep Reinforcement Learning | A Supervised Learning Framework for Modeling Director Agent Strategies in Educational Interactive Narrative | Blue scale: Early detection of impending congestive heart failure events via wireless daily self-monitoring | eng_Latn | 20,195 |
Lessons Learned from AlphaGo | Bandit Based Monte-Carlo Planning | World-Championship-Caliber Scrabble | eng_Latn | 20,196 |
Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving | Markov Games as a Framework for Multi-Agent Reinforcement Learning | Key2Vec: Automatic Ranked Keyphrase Extraction from Scientific Articles using Phrase Embeddings | eng_Latn | 20,197 |
A Multi-Armed Bandit Approach for Online Expert Selection in Markov Decision Processes | End-to-End Training of Deep Visuomotor Policies | Hydroxycinnamic Acid Antioxidants: An Electrochemical Overview | kor_Hang | 20,198 |
BOOK: Storing Algorithm-Invariant Episodes for Deep Reinforcement Learning. | Deep Reinforcement Learning with Double Q-learning | interference cancellation for cellular systems : a contemporary overview . | eng_Latn | 20,199 |
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