Work2018

Computational Model for Human Decision Making: A Study of Prospect Theory

Nimisha Gupta · Mitul Kumar Ahirwal · Mithilesh Atulkar

7 citations0/0 files storedIEEE Conference on Information and Communication Technology (CICT)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Decision-Making and Behavioral Economics Experimental Behavioral Economics Studies Leadership, Behavior, and Decision-Making Studies

Abstract

Decision making can be defined as a process of selecting best alternatives among several possible alternatives. In this paper, two decision making theories are compared with the decision of several humans. Decision making theories used in this paper are Expected Utility Theory (EUT) and Prospect Theory (PT). Results are obtained and compared over the examples of gambles. Each example of gamble offers the choice with certainty and uncertainty. The purpose of this paper is to explain how people behave while making decision and how decision making theories predict the decision of peoples.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 7 citations exist upstream.

References

1979Prospect Theory: An Analysis of Decision under Risk 1992Advances in prospect theory: Cumulative representation of uncertainty 1995Weighing risk and uncertainty.1994Violations of the betweenness axiom and nonlinearity in probability 1995Risk attitudes and decision weights 1993An axiomatization of cumulative prospect theory 2006A survey of decision support system applications (1995–2001)1989Retrospective on the utility theory of von Neumann and Morgenstern

Cited by

2022Development of human decision making model with consideration of human factors through reinforcement learning and prospect utility theory 2024Refining of Learning in Human Decision Making Models: A Simple Step towards Machine Unlearning

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.