## Systema: Whyever? Part 3

Considering the definition of strategy that I have adopted in part 2 of this discussion, I also want to adopt a new definition for “tactics” and “operations”. The definitions would be as follows:

goals: the beginning, intermediate and terminal states of a system.

strategy: a single path to a terminal goal observing the rules.

motivation: the complete set of strategies for a system.

tactics: the actual path followed during an actual session by a user or users.

Note: I have changed the definition of operation and added result based on the comment by Rita Heinlein. – relationary

operation: the actual non-navigational rule with parameters found in a tactical path.

result: the actual goal state achieved by an operation found in a tactical path.

With all the above considered I would suggest that information architecture be renamed to motivational modeling.

## Systema: Whyever? Part 2

Part 1 is here.

strategy (n)

4. a plan, method, or series of maneuvers or stratagems for obtaining a specific goal or result: a strategy for getting ahead in the world.

goal (n)

1.the result or achievement toward which effort is directed; aim; end.

rule (n)

1. a principle or regulation governing conduct, action, procedure, arrangement, etc.: the rules of chess.

An extensive form game is a specification of a game in game theory. This form represents the game as a tree. Each node (called a decision node) represents every possible state of play of the game as it is played. Play begins at a unique initial node, and flows through the tree along a path determined by the players until a terminal node is reached, where play ends and payoffs are assigned to all players. Each non-terminal node belongs to a player; that player chooses among the possible moves at that node, each possible move is an edge leading from that node to another node.

It should be noted that even in a game with a finite number of moves (steps) there are generally countless strategies (paths).

Looking at the Extensive Form diagram above and considering the definitions, we can see that the game above has two players: 1 and 2. The numbers by every non-terminal node indicate to which player that decision node belongs. The numbers by every terminal node represent the payoffs to the players (e.g. 2,1 represents a payoff of 2 to player 1 and a payoff of 1 to player 2). The labels by every edge of the graph are the name of the action that that edge represents.

I would like to play with the terminology. I would call the nodes “goals”, I would call the edges “rules” and the paths I would call “strategies”. Goals are actually states of the system and the rules are actually processes. Thinking about it this way makes me think of information architecture and website architecture. Browsing and navigation in this case becomes a one player strategy where the website provides the goals and rule set. However, the design process of the system is to determine the goal set and rule set of the player and provide a “natural” or even more optimal set of strategies for the user to follow.

Part 3 is here.

## Systema: Whyever? Part 1

Over the past few weeks I have been reflecting on the concept of a Business Motivation Model and have thought about it in the context of physics as “cause”. The Business Rules Group attempted to create a Business Motivation Model, but I came to the conclusion they have failed. When they should have been attempting to create a notational system, they instead came up with a generalized business model.

The purpose of the “Why” focus in the Zachman Framework and correspondingly the Six Hats, Six Coats Framework, is to gauge the order of the system. The Green Hat row and Green Coat Column describe how legalistic the system is–how many causes a system contains.

The best way to think about the causality of a system is not business rules, but game theory. In particular, causality as a three dimensional network relating strategies. A good Business Motivation Model notation would allow the modeler to represent the strategies of all parties, how they interact and the expected outcomes. The Extensive Form Game notation is a good start but I think with some work I could come up with something better.

Part 2 here.

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