Results 51 to 60 of about 12,386 (222)
State‐Dependent Market (In)Efficiency in Cryptocurrency Markets
Journal of Futures Markets, EarlyView.ABSTRACT This paper develops a meta‐learning framework to test whether cryptocurrency market inefficiency is static or state‐dependent. To resolve competing claims between the Efficient and Adaptive Market Hypotheses (AMH), we construct an adaptive trading strategy using high‐frequency data for 50 major cryptocurrencies.
Sasan Barak +2 more
wiley +1 more source
Undiscounted bandit games [PDF]
Games and Economic Behavior, 2020 We analyze undiscounted continuous-time games of strategic experimentation with two-armed bandits. The risky arm generates payoffs according to a Lévy process with an unknown average payoff per unit of time which nature draws from an arbitrary finite set.
Keller, G, Rady, S
openaire +5 more sources
Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch
Naval Research Logistics (NRL), EarlyView.ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley +1 more source
CoRR, 2014 Can an intelligent jammer learn and adapt to unknown environments in an electronic warfare-type scenario? In this paper, we answer this question in the positive, by developing a cognitive jammer that adaptively and optimally disrupts the communication between a victim transmitter-receiver pair.
SaiDhiraj Amuru +3 more
openaire +3 more sources
, 2021 Contextual bandits algorithms have become essential in real-world user interaction problems in recent years. However, these algorithms represent context as attribute value representation, which makes them infeasible for real world domains like social ...
Ravindran, Balaraman +2 more
core +1 more source
Bootstrap Thompson Sampling and Sequential Decision Problems in the Behavioral Sciences
SAGE Open, 2019 Behavioral scientists are increasingly able to conduct randomized experiments in settings that enable rapidly updating probabilities of assignment to treatments (i.e., arms).
Dean Eckles, Maurits Kaptein
doaj +1 more source
Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
SmartBot, EarlyView.Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source
Architects, Bandits and Knights
Проект Байкал, 2006 Some quotations: «A new disaster has been added to pollution of the unique lake–it is cottage development of the coast». «The trouble is that the projects are realized without even being seen by architectural society.
Konstantin Lidin
doaj +1 more source
Highly Configurable Evolutionary Multi‐Objective Optimisation and Application in UAV Path Planning
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Multi‐objective optimisation is crucial in engineering and real‐world decision‐making. Although traditional decomposition‐based approaches such as MOEA/D yield reasonable results, they depend heavily on expert knowledge. Existing MetaBBO approaches partially alleviate this reliance, however, they offer limited configurability and lack real ...
Kaixu Chen +4 more
wiley +1 more source
Non-Stationary Representation Learning in Sequential Linear Bandits
IEEE Open Journal of Control Systems, 2022 In this paper, we study representation learning for multi-task decision-making in non-stationary environments. We consider the framework of sequential linear bandits, where the agent performs a series of tasks drawn from different environments.
Yuzhen Qin +4 more
doaj +1 more source