The Behavior of Organisms: An Experimental Analysis
By F. Nowell Jones, B. Skinner. 2016
2,091 citations recorded by the source corpus.
Subfields: Developmental and Educational Psychology, Ecology, Evolution, Behavior and Systematics, Experimental and Cognitive Psychology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Developmental and Educational Psychology
- Susan A. Murphy
- Thore Graepel
- Doina Precup
- Justin Cheng
- Peter Stone
- Michael L. Littman
- B. Casey
- David Silver
In Ecology, Evolution, Behavior and Systematics
- Peter Stone
- B. Casey
- Jure Leskovec
- Pei-Luen Patrick Rau
- Sebastian Risi
- Kenneth O. Stanley
- Na Sun
- Liang Ma
In Experimental and Cognitive Psychology
- L. Mehrkam
- Cristian Danescu-Niculescu-Mizil
- Susan A. Murphy
- Peter Stone
- Michael L. Littman
- B. Casey
- Yulia Tsvetkov
- Thore Graepel
Citations in the corpus
- Deep Reinforcement Learning for Autonomous Driving: A Survey (2020, background): “Skinner [45] discovered while training a rat to push a lever that any movement in the direction of the lever had to be rewarded to encourage the rat to complete the task.”
- Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, background): “ing is an old and intuitive notion. Scientific evidence of animal learning from experience was documented initially in the works of behaviorism with scientists such as Thorndike (1911), Pavlov (1927), Skinner (1938, 1953), and Hull (1943).The main idea was to experiment and verify scientifically how e”
- Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces (2017, background): “Another area of research that aims to use explicit human interaction to increase the speed at which autonomous agents can learn to perform tasks is that of reward shaping (Skinner 1938; Randløv and Alstrøm 1998; Ng, Harada, and Russell 1999; Devlin and Kudenko 2012).”
- Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning (2015, background): “Skinner introduced operant conditioning, a concept of providing feedback to modify the frequency of voluntary behaviors [23].”
- Learning From Explanations Using Sentiment and Advice in RL (2017, background): “Reinforcement learning (RL) is a form of machine learning influenced by behavioral psychology in which an agent learns what actions to take by receiving rewards or punishments from its environment [18], [21].”
- Behavioral differences among breeds of domestic dogs (Canis lupus familiaris): Current status of the science (2014, background): “In this case, we might argue that territorial aggression is maintained by negative reinforcement (the removal of an aversive stimulus contingent on aggressive responses, increasing the probability that aggressive responses will be exhibited in the future) (Skinner, 1938).”
- Is it all a game? Understanding the principles of gamification (2015, background): “First, both positive and negative reinforcements encourage repetition of behaviors, as operant conditioning (Skinner, 1938) and the law of effect (Thorndike, 1905) show us.”
- Gender Socialization during Adolescence in Low- and Middle-Income Countries : Conceptualization, influences and outcomes (2017, background): “Inspired by theoretical contributions from behavioural psychologists, Skinner (1938) and Hull (1935), proponents of this viewpoint, saw ‘reinforcement’ as the central process in habit formation.”
- A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games (2016, background): “tion, the probability is increased that they will act similarly in similar situations in the future. This is described by principles such as the law of effect (Thorndike, 1898), operant conditioning (Skinner, 1938) and trial-and-error learning (Thorpe, 1979) in behaviorist psychology, and has inspir”
- Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support (2017, background): “, identifying and immediately reinforcing successively improving approximations of the target behavior [43, 44]) and teachable”
- Learning from Demonstration for Shaping through Inverse Reinforcement Learning (2016, background): “Reward shaping, derived from behavioral psychology [20], is a way of incorporating prior knowledge in the learning process.”
- How Community Feedback Shapes User Behavior (2014, background): “This means that negative feedback seems to have exactly the opposite effect than predicted by the operant conditioning framework (Skinner 1938).”
- Symmetry Learning for Function Approximation in Reinforcement Learning (2017, background): “The notion of reward shaping in RL has its roots in behavioral psychology [20].”