Bachelor of Science in Decision Theory (B.S.D.T.)

The Bachelor of Science in Decision Theory provides a comprehensive exploration of decision-making frameworks, cognitive processes, and mathematical models that shape human and artificial decision-making. This program is designed for students who want to gain expertise in rational choice theory, probabilistic reasoning, and strategic decision analysis, preparing them to navigate complex systems in areas like economics, artificial intelligence, business strategy, and cognitive science.

About the Program

The Bachelor of Science in Decision Theory equips students with the analytical and critical thinking skills needed to understand and model decision-making in uncertain environments. The program combines cognitive science, mathematics, and behavioral economics with cutting-edge applications in artificial intelligence and strategic planning. Students will engage with real-world case studies and advanced computational tools to develop innovative solutions for decision-making challenges in various fields.

The curriculum covers core topics such as game theory, cognitive decision modeling, risk assessment, and Bayesian inference. This interdisciplinary approach ensures that graduates are equipped to design decision-support systems and optimize strategic choices in both human and machine contexts.

Key Areas of Study

  • Rational Choice Theory and Decision Models
  • Game Theory and Strategic Analysis
  • Probabilistic Reasoning and Bayesian Inference
  • Cognitive Processes in Decision-Making
  • Risk Assessment and Optimization

Core Curriculum & Program Structure

Program Courses: 120 credits

Degree Requirements

Total Credits Required: 120 credits

Core Major Courses: 40 credits

Electives & Research Focus: 30 credits

General Education & Interdisciplinary Studies: 50 credits

Fall Semester 1

QCO 101 – Introduction to Quantum Cognition (3 credits)

CEN 101 – Introduction to Cognitive Engineering (3 credits)

LOG 101 – Foundations of Logic (3 credits)

General Education Elective (3 credits)

Research & Writing Foundations (3 credits)

Spring Semester 2

QCO 102 – Probabilistic Reasoning in Cognition (3 credits)

CEN 204 – Risk and Decision Modeling (3 credits)

LOG 203 – Advanced Game Theory (3 credits)

General Education Elective (3 credits)

Introduction to Behavioral Science (3 credits)

Fall Semester 3

QCO 201 – Bayesian Cognitive Models (3 credits)

LOG 202 – Logical Structures in Decision Systems (3 credits)

CEN 305 – Computational Logic and Decision Systems (3 credits)

Research Elective in Decision Science (3 credits)

General Education Elective (3 credits)

Spring Semester 4

LOG 204 – Decision-Making in Multi-Agent Systems (3 credits)

DT 202 – Behavioral Economics and Decision Science (3 credits)

DT 203 – Computational Decision Models (3 credits)

Research Elective in Probabilistic Reasoning (3 credits)

General Education Elective (3 credits)

Fall Semester 5

DT 301 – Decision Optimization and Operations Research (3 credits)

DT 302 – Cognitive Bias and Decision Errors (3 credits)

DT 303 – Game Theory in Economics and Strategy (3 credits)

Elective in Cognitive Science or AI (3 credits)

General Education Elective (3 credits)

Spring Semester 6

DT 304 – Advanced Topics in Decision Theory (3 credits)

DT 305 – Risk Management and Scenario Planning (3 credits)

DT 306 – Machine Learning for Decision Support (3 credits)

Research Elective in Decision Science (3 credits)

General Education Elective (3 credits)

Fall Semester 7

LOG 404 – Senior Seminar: Logic and Decision Science (3 credits)

DT 401 – Independent Research in Decision Theory (3 credits)

DT 402 – Decision-Making in Complex Systems (3 credits)

Research Elective in Decision Theory (3 credits)

General Education Elective (3 credits)

Spring Semester 8

DT 404 – Capstone Project: Decision Modeling & Optimization (6 credits)

DT 405 – Ethics and Decision-Making in AI (3 credits)

Final Research Elective or Internship (3 credits)

General Education Elective (3 credits)