The Power Of Reinforcement

2004 CHOICE Outstanding Academic Title According to Stephen Ray Flora, reinforcement is a very powerful tool for improving the human condition despite often being dismissed as regarding people as less than human and as "overly simplistic." This book addresses and defends the use of reinforcement principles against a wide variety of attacks. Countering the myths, criticisms, and misrepresentations of reinforcement, including false claims that reinforcement is "rat psychology," the author shows that building reinforcement theory on basic laboratory research is a strength, not a weakness, and allows unlimited applications to human situations as it promotes well-being and productivity. Also examined are reinforcement contingencies, planned or accidental, as they shape behavioral patterns and repertoires in a positive way.

The classic bestseller on performance management is updated to reflect changes in today's working environment. When an employer needs to know how to gain maximum performance from employees, renowned behavioral psychologist--Aubrey Daniels is the man to consult. What has made Daniels the man with the answers? His ability to apply scientifically based behavioral stimuli to the workplace while making it fun at the same time. Now Daniels updates his ground-breaking book with the latest and best motivational methods, perfected at such companies as Xerox, 3M, and Kodak. All-new material shows how to: create effective recognition and rewards systems in line with today's employees want; Stimulate innovations and creativity in new and exciting ways; overcome problems associated with poorly educated workers; motivate young employees from the minute they join the workforce.

Training the Best Dog Ever, originally published in hardcover as The Love That Dog Training Program, is a book based on love and kindness. It features a program of positive reinforcement and no-fail techniques that author Dawn Sylvia-Stasiewicz used to train the White House dog, Bo Obama, and each of Senator Ted Kennedy’s dogs, among countless others. Training the Best Dog Ever relies on trust and treats, not choke collars; on bonding, not leash-yanking or reprimanding. The five-week training program takes only 10 to 20 minutes of practice a day and works both for puppies and for adult dogs that need to be trained out of bad habits. Illustrated with step-by-step photographs, the book covers hand-feeding; crate and potty training; and basic cues—sit, stay, come here—as well as more complex goals, such as bite inhibition and water safety. It shows how to avoid or correct typical behavior problems, including jumping, barking, and leash-pulling. Plus: how to make your dog comfortable in the world—a dog that knows how to behave in a vet’s office, is at ease around strangers, and more. In other words, the best dog ever.

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

The contingent relationship between actions and their consequences lies at the heart of Skinner’s experimental analysis of behavior. Particular patterns of behavior emerge depending upon the contingencies established. Ferster and Skinner examined the effects of different schedules of reinforcement on behavior. An extraordinary work, Schedules of Reinforcement represents over 70,000 hours of research primarily with pigeons, though the principles have now been experimentally verified with many species including human beings. At first glance, the book appears to be an atlas of schedules. And so it is, the most exhaustive in existence. But it is also a reminder of the power of describing and explaining behavior through an analysis of measurable and manipulative behavior-environment relations without appealing to physiological mechanisms in the brain. As en exemplar and source for the further study of behavioral phenomena, the book illustrates the scientific philosophy that Skinner and Ferster adopted: that a science is best built from the ground up, from a firm foundation of facts that can eventually be summarized as scientific laws.