Research and Development

Research and Development Projects

Witnesses may have speaking patterns (for example giving only ‘or’ or ‘and’ statements) that can be noticed by going through different cases, so the long term success of the detective depends on the development of a questioning strategy and the ability to categorize the set of suspects.

This game supplements instructions in logic: false, true statements, truth tables, logical inferences, operations on sets, categorization, conjecture making, proofs, etc.

Current Projects Include:

The current Educational Game Research Institute (Egris) R&D activities include games and robotic projects design, implementation, classroom testing, and presentations focused on math and science education. These activities can be broken into:

Creating topic related, engaging, video game segments and robotics experiments (using a game engine) that aid in teaching mathematics, computer science, and the general sciences.

Formally verifying the efficacy of these game segments and experiments in the post-secondary classroom environment.

Presenting the material and activities to better determine appropriateness for different environments.

The concept of a “topic” related game segment:
Each game segment will focus on a topic usable in multiple types of courses. A few examples include the distributive law from algebra used in many different science courses, the vector “dot” product used in math, physics, and engineering, chemical equations and the periodic table, and sorting concepts from math and computer science.

The creation of these segments and experiments are a combined ongoing effort using students, appropriate educators, and our small in-house management team for the game design phase, and primarily students under our management for game development and technical support.

The formal verification of effectiveness, in the form of classroom analysis, includes both student and faculty research teams under our guidance. Much of the field work will occur during the school year though some analysis will occur during the summers.

Ace Altro: An online crime drama logic game, where the ultimate goal is to solve a mystery, ‘Who done it?’. A player/detective can evaluate statements of witnesses that are given in everyday language describing what they know about the crime. Using symbolic logic the player translates the statements into logical sentences and evaluates the outcome against the collected evidence and the set of suspects. The complexity of the statements, suspects’ diversity and evidence varies depending on the age/level of the player.

Rock, Paper, Scissors (RPS)
RPS (also known as jan-ken-po, rochambeau or roshambo, ching-chang-wulla, …), is based on the well known children’s game, where, with the uniform probabilities (of 1/3), two players pick simultaneously a rock, paper, or scissors:

If both players pick the same object, there is a tie. This is a zero sum game theory game (the only equilibrium is in mixed strategies).

The game can be played with skill if the game extends over many sessions, as a player can often recognize and exploit the non-random behavior of an opponent. Then it is up to a player to determine the best competing strategy. In this case, when playing against the computer, the computer can create random strategies, each strategy lasting over many sessions. The game supports probability and statistics curriculum, data analysis, decision trees, strategic choices, etc.

Rock wins over scissors

Paper wins over rock

Scissors wins over paper

RPS Payoff Grid/ Scoring Table

Ice Race: Ice Race, still in its infancy, is a race across a large body of water with multiple obstacles played by one or more players. It is used to demonstrate basic vector analysis. The player develops a comfort level with vectors including vector addition, subtraction, dot product and cross product.

Game Engine Robotics Project: This activity uses an inexpensive Game Engine, a relational DBMS, and Rex, a student - faculty created robot, to simultaneously both simulate and control robots.

Near-term objective: Low-cost STEM (Science, Technology, Engineering, and Mathematics) teaching tools. Various team based projects are used as teaching tools. The students develop a comfort level with relational DBMSs, high level, embedded, and real-time programming, vector analysis, kinematics, graph theory, collision detection/resolution, AI, basic physics and mechanics, etc.

Monster Sort: a combinatorial game that asks students to develop their own searching and sorting strategies and compete with each other, or the computer character, monster Gork, sorting and/or searching for numbered boxes. Numbered boxes can be randomly or sequentially ordered. Several parameters are evaluated: memory usage, steps required to complete, complexity, etc. Students have full access to the data, and can make their decisions to maximize the chances of success. This game supplements school curricula in combinatorics, probability, algorithm development, decision making strategies, computer programming, etc.

Simple example: Put boxes numbered 5,4,1,2,3 in increasing order.

Possible solution: move 5 to the side (store in the memory). Put 1 in the first spot, now the third spot is empty. Move 3 to the third spot. Move 5 to the last spot. Put 4 to the side, move 2 to the second spot, and move 4 from storage.

Number of steps: 7
Memory (storage) use: 1 unit

Depending on the initial distribution of numbers and the choice of parameters (such as storage costs, number of steps, and time) the student can hand craft an optimal solution, and, with experience, will develop winning strategies.

When the student plays against Gork (the computer), Gork will use a standard sorting technique such as Insertion Sort. How does that compare to the student’s hand-crafted sort? Can the student create an algorithmic sort (using a relatively simple algorithm language) that is better than Gork’s standard sorting techniques? What does better mean? What are the tradeoff’s in different sorting strategies (e.g. Insertion Sort, Quick Sort, etc.) and the student’s sorting algorithm?

Ultimate research objective: groups of 1 to 200 low-cost, multifunctional robots working together in:

1.	Agriculture/environment (fruit/vegetable picking; pest management; water/fertilizer management; yard/garden maintenance, …)
2.	Industry (safety/security, parking patrol, inventory management, maintenance, …)
3.	The home (in-home care, …)

Currently completing Phase II - Demonstrate a robot architecture (Rex) that supports:

1.	Inexpensive research test bed and classroom STEM teaching tool
2.	Centrally managed manual and/or automated control via wifi
3.	Local level reflex autonomy and intelligence
4.	Independent “plug-and-play” sensors, motors, arms, …
5.	Multi-directional motion, multi DOF arm(s) and effector(s)
6.	Vision, ultrasound, GPS, … for environmental, positional and directional knowledge
7.	AI, FSMs, path finding, collision detection and avoidance
8.	RFID, solar, …
9.	Can support fault tolerance and/or redundancy