Signals, Models & Actions

(awffwmod01: draft v3)

Contents


Introduction

Feature model

Competitive advantage in <system> can take the form of:


Structural Model

The structural model should be in line with Porter's ideas on structural constraints. 

Forces seem to equate to <?>. 


Components:
  1. Regulations & Rules (Basic Physics/Government)
  2. Physical & Meme Resources and supplies
  3. Iterative irreversible moves & mistakes (CAS chance event)
  4. New Competitors -> access and command of environment
  5. New memes - theory applied in operations (New Technology)

Regulations & Rules (Basic Physics/Government)


Physical & Meme Resources and supplies

Each agent is associated with a small number of phenomena based on the rules


Iterative irreversible moves & mistakes (CAS chance event)

It is difficult to avoid gross errors. 

Use of experience (search strategies) and learning (modeling) can enable use of a default hierarchy of special tests to avoid traps. 

New Competitors -> access and command of the environment



New memes - theory applied in operations (New Technology)

Logistics & Combinations (Value delivery System)

Situation

SWOT analysis

provides a process for associative integration of forces and strategies. Over time the recall of these associations provides the model schemata that can be reorganized by second level genetic operators.  

Dynamic Model

The business models of dynamic strategy seem to borrow from Chess - Opening, Middle and End Game. 


CAS Model

CAS systems use models and actions to respond to signals.  Operating within a mechanism for responding to the signals in the environment a control structure & plan can specifically select model representations that run in parallel to assess if the situation corresponds to their model.  The modeling operation's conclusions can then be used to make judgments about actions to be taken.  Once the actions have been effected the signals can be re-sampled and modeled in a PDCA Shewhart cycle

CAS systems are emergent.  All aspects of the system are based on phenomena (the rules) associated through agents with the building blocks from which the system is deployed.  In the case of chess the epiphenomena are all instantiated through human action.  The emergent components induce signals through complementary interactions with schemata and models in the agent's minds of the board structures and the competing player.  A competitor with effective models of the board structure can select a high value action that enables the desired phenomena to be

Stage setting move sequence analyses: