Kalsnet (KNet) Consulting Group | AI • Cyber • Agentic-Systems/Rational-Theory Applications
Streamlit that combines Rational Choice / Multi-Criteria Decision Analysis (MCDA) and Game Theory to enable structured, transparent, and data-driven decision-making. The application evaluates multiple alternatives using criteria, scores, and weighted priorities, calculates Expected Utility, and produces a ranked recommendation identifying the most favorable option. Its **Game Theory** component models **two-player strategic interactions** using **payoff matrices and identifies Pure-Strategy Nash Equilibria and Strictly Dominant Strategies. The framework leverages **Pandas**, **NumPy**, **Matplotlib**, and **Seaborn** for data processing, mathematical analysis, ' statistical computation, visualization, rankings, and heatmaps. Users can generate Synthetic Data for demonstrations or upload their own CSV/TXT datasets for customized analysis.The application provides an intuitive interactive dashboard, maintains analytical results using Streamlit Session State, and supports scenario analysis by allowing users to adjust criteria weights and strategic payoffs. Results can be exported as CSV, TXT, Microsoft Word, and PDF reports for management review and decision documentation. In real-world environments, the framework can support Defense and Government Decision-Making, Cybersecurity Strategy, Technology Selection, Risk-Based Decision Making, Resource Allocation, Vendor Evaluation, Policy Analysis, and Strategic Planning, providing organizations with a repeatable and explainable approach for analyzing complex decisions and competitive strategic situations.
Launch AppThe Rational Decision Support System applies Rational Choice Theory and Expected Utility Theory to three real-world decision domains, turning subjective judgment calls into transparent, defensible, data-driven recommendations. 1. In Strategic Decision-Making, it scores competing strategic alternatives against weighted criteria using Multi-Attribute Utility Theory, then ranks them so leadership can see exactly which option maximizes expected utility and why. 2. In Resource Allocation, it solves a constrained linear program to distribute a limited budget across competing initiatives, balancing expected payoff against risk while respecting minimum and maximum funding limits. 3. In Threat Assessment, it scores each threat as Likelihood times Impact, buckets it into Low/Medium/High/Critical, and produces a prioritized register so security or risk teams can focus resources where expected cost is greatest. Across all three modules, the app supports synthetic demo data or real CSV/XLSX uploads, interactive visualizations, and one-click export to PDF, Word, TXT, and CSV for reporting. Together, these use cases give an organization one consistent, theory-grounded framework for making, allocating, and defending high-stakes decisions.
Launch