Results 91 to 100 of about 52,961 (314)

Using course credit as reinforcement for free-style study behavior

open access: yes, 1975
Ninety students in an introductory psychology course were each assigned to one of three matched groups, which were levels of multiple-baseline format. For each level, a simple within subjects reversal design was used, in which points were awarded for ...
Kizer, Philip L.
core  

Too Complex to Choose? The Role of Heuristics in Shaping Farmers' Willingness to Pay for Income Stabilization Tool in Italy

open access: yesAgribusiness, EarlyView.
ABSTRACT European agriculture is increasingly exposed to economic instability driven by extreme weather events, market volatility, and geopolitical tensions. To manage these growing risks, farmers are encouraged to adopt innovative risk management strategies such as the Income Stabilization Tool (IST), which offers protection against severe income ...
Alice Stiletto   +5 more
wiley   +1 more source

ChatGPT: perspectives from human–computer interaction and psychology

open access: yesFrontiers in Artificial Intelligence
The release of GPT-4 has garnered widespread attention across various fields, signaling the impending widespread adoption and application of Large Language Models (LLMs). However, previous research has predominantly focused on the technical principles of
Jiaxi Liu
doaj   +1 more source

Behavioral contrast : distribution of responses and time in a two-component multiple schedule of reinforcement [PDF]

open access: yes, 1974
The concurrent properties of component performances on multiple variable-interval schedules of reinforcement were studied in six pigeons under conditions where pecks in each component of a two-component multiple schedule were reinforced according to ...
Hughes, Ronald Granger   +1 more
core  

Darwin in mind : new opportunities for evolutionary psychology

open access: yes, 2011
Evolutionary Psychology (EP) views the human mind as organized into many modules, each underpinned by psychological adaptations designed to solve problems faced by our Pleistocene ancestors.
Bolhuis Johan J.   +15 more
core   +1 more source

Reinforcement learning or active inference? [PDF]

open access: yes, 2009
This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception.
Friston, K.   +17 more
core   +1 more source

Is There a Market for Organic Milk in Serbia? Insights From Integrated Choice and Latent Variable Model

open access: yesAgribusiness, EarlyView.
ABSTRACT Past growth in the global organic market has been concentrated in high‐income countries, while in middle‐income countries such as Serbia the organic market remains nascent and characterized by a sparse assortment of organic products, high retail premia and limited evidence on consumer preferences and their drivers.
Milan Tatic   +3 more
wiley   +1 more source

Haste or Speed? Alterations in the Impact of Incentive Cues on Task Performance in Remitted and Depressed Patients With Bipolar Disorder

open access: yesFrontiers in Psychiatry, 2018
A variety of evidence suggests that bipolar disorder is associated with disruptions of reward related processes, although the properties, and scope of these changes are not well understood.
Henry W. Chase   +6 more
doaj   +1 more source

The effects of verbal consequences for rule-following on sensitivity to programmed contingencies of reinforcement [PDF]

open access: yes, 1991
This study examined the effects of two types of verbal consequences for rule-following and their impact on subject's responses to programmed schedules of reinforcement.
Hass, Joseph Raymond   +1 more
core  

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang   +6 more
wiley   +1 more source

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