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17,841
Managerial Discretion and Optimal Financing Policies
- J. Finan. Econ
, 1990
"... I analyze financing policies in a firm owned by atomistic shareholders who observe neither cash flows nor management’s investment decisions. Management derives perquisites from investment and invests as much as possible. Since it always claims that cash flow is too low to fund all positive net prese ..."
Abstract
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Cited by 453 (18 self)
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I analyze financing policies in a firm owned by atomistic shareholders who observe neither cash flows nor management’s investment decisions. Management derives perquisites from investment and invests as much as possible. Since it always claims that cash flow is too low to fund all positive net
Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks
- IEEE Transactions on Automatic Control
, 1992
"... Abstruct-The stability of a queueing network with interdependent servers is considered. The dependency of servers is described by the definition of their subsets that can be activated simultaneously. Multihop packet radio networks (PRN’s) provide a motivation for the consideration of this system. We ..."
Abstract
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Cited by 949 (19 self)
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is stable. A policy m,, is obtained which is optimal in the sense that its stability region Cn0 is a superset of the stability region of every other scheduling policy. The stability region Cmo is characterized. Finally, we study the behavior of the network for arrival rates that lie outside the stability
Finite-time analysis of the multiarmed bandit problem
- Machine Learning
, 2002
"... Abstract. Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while taking the empirically best action as often as possible. A popular measure of a policy’s success in addressing ..."
Abstract
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Cited by 817 (15 self)
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this dilemma is the regret, that is the loss due to the fact that the globally optimal policy is not followed all the times. One of the simplest examples of the exploration/exploitation dilemma is the multi-armed bandit problem. Lai and Robbins were the first ones to show that the regret for this problem has
Markov games as a framework for multi-agent reinforcement learning
- IN PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING
, 1994
"... In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed in their behavior ..."
Abstract
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Cited by 601 (13 self)
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-learning-like algorithm for finding optimal policies and demonstrates its application to a simple two-player game in which the optimal policy is probabilistic.
Coverage Control for Mobile Sensing Networks
, 2002
"... This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functio ..."
Abstract
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Cited by 582 (49 self)
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functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
What Can Economists Learn from Happiness Research?
- FORTHCOMING IN JOURNAL OF ECONOMIC LITERATURE
, 2002
"... Happiness is generally considered to be an ultimate goal in life; virtually everybody wants to be happy. The United States Declaration of Independence of 1776 takes it as a self-evident truth that the “pursuit of happiness” is an “unalienable right”, comparable to life and liberty. It follows that e ..."
Abstract
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Cited by 545 (24 self)
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for economists to consider happiness. The first is economic policy. At the micro-level, it is often impossible to make a Pareto-optimal proposal, because a social action entails costs for some individuals. Hence an evaluation of the net effects, in terms of individual utilities, is needed. On an aggregate level
Decision-Theoretic Planning: Structural Assumptions and Computational Leverage
- JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1999
"... Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions and perspectives ..."
Abstract
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Cited by 515 (4 self)
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-related methods, showing how they provide a unifying framework for modeling many classes of planning problems studied in AI. It also describes structural properties of MDPs that, when exhibited by particular classes of problems, can be exploited in the construction of optimal or approximately optimal policies
The click modular router
, 2001
"... Click is a new software architecture for building flexible and configurable routers. A Click router is assembled from packet processing modules called elements. Individual elements implement simple router functions like packet classification, queueing, scheduling, and interfacing with network devic ..."
Abstract
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Cited by 1167 (28 self)
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language tools that optimize router configurations and ensure they satisfy simple invariants. Due to Click’s architecture and language, Click router configurations are modular and easy to extend. A standards-compliant Click IP router has sixteen elements on its forwarding path. We present extensions
Motivation through the Design of Work: Test of a Theory. Organizational Behavior and Human Performance,
, 1976
"... A model is proposed that specifies the conditions under which individuals will become internally motivated to perform effectively on their jobs. The model focuses on the interaction among three classes of variables: (a) the psychological states of employees that must be present for internally motiv ..."
Abstract
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Cited by 622 (2 self)
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under government sponsorship are encouraged to express their own judgment freely, this report does not necessarily represent the official opinion or policy of the government. redesign are not fully adequate to meet the problems encountered in their application. Especially troublesome is the paucity
Policy gradient methods for reinforcement learning with function approximation.
- In NIPS,
, 1999
"... Abstract Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly repres ..."
Abstract
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Cited by 439 (20 self)
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that the gradient can be written in a form suitable for estimation from experience aided by an approximate action-value or advantage function. Using this result, we prove for the first time that a version of policy iteration with arbitrary differentiable function approximation is convergent to a locally optimal
Results 1 - 10
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17,841
