Tuesday, February 23, 2016

Python's Installation Path

Python's Installation Path

>>> import os
>>> import sys
>>> os.path.dirname(sys.executable)
'C:\\Users\\Roosta\\AppData\\Local\\Programs\\Python\\Python35-32'


Sunday, February 21, 2016

███ BizHawk ███

BizHawk 

BizHawk is a multi-platform emulator with full rerecording support and Lua scripting. BizHawk focuses on core accuracy and power user tools while still being an easy-to-use emulator for casual gaming. 

It is BizHawk. BizHawk is a multi-platform emulator with full rerecording support and Lua scripting. BizHawk focuses on core accuracy and power user tools while still being an easy-to-use emulator for casual gaming.
BizHawk
BizHawk Web Page: http://tasvideos.org/BizHawk.html 


Sunday, February 14, 2016

███ Evolutionary Algorithms ███

Evolutionary Algorithms

In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the quality of the solutions (see also loss function). Evolution of the population then takes place after the repeated application of the above operators. Artificial evolution (AE) describes a process involving individual evolutionary algorithms; EAs are individual components that participate in an Artificial Evolution [ref].

The most extensive Evolutionary Algorithm (EA) has started billions of years ago with the Big Bang. Thanks to it humanity evolved just recently and is able to enjoy all those other mind-blowing things that arose at the same time. Thus it is no wonder that one day someone had the idea to model the principles of evolution and use it for solving complex problems. Evolutionary Algorithm (EA) is the umbrella term for all computational models that are inspired by evolutionary mechanisms. There is a variety of implementations of EAs available. The most important ones are Genetic Algorithms (GAs), Genetic Programming (GP), Evolutionary Programming (EP), Classifier Systems and Artificial Life (AI). Although the particular representations can heavily differ from each other they all share basic principles. Every algorithm organizes a population of individuals (e.g. construction plans, configuration data, DNA ...). The individuals are developed through mutation and crossover operations and then evaluated by measuring their fitness that indicates how good they fit into their environment. Problems to be solved are defined by the shape of the fitness landscape [ref].

 
In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm.
Evolutionary Algorithms




Metaheuristics

Metaheuristics (Metaheuristic Algorithms [MAs])

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity [ref]. In short, metaheuristics can be summarized as follows:

• MAs employ strategies to effectively perform a search process and to efficiently explore the search space such that near-optimal or optimal solutions are obtained. 
• The search mechanisms in MAs range from simple local search procedures to complex learning processes. 
• MAs provide approximate solutions and are usually nondeterministic. 
• They may incorporate escape mechanisms such as niching and stretching in order to avoid getting trapped in confined areas of the search space. 
• Metaheuristics are not problem specific. 

Based on the aforementioned discussion, metaheuristics can be considered as a set of algorithmic concepts that can be used to define heuristic methods applicable to a wide range of problems. In other words, they (metaheuristics) are a general purpose algorithmic framework applicable to a wide range of problems with relatively fewer modifications (Dorigo et al., 2006). Some of the well-known MAs include tabu search (TS) (Glover, 1989, 1990), genetic algorithms (GAs) (Goldberg, 1989), simulated annealing (SA) (Kirkpatrick et al., 1983), ant colony optimization (ACO) (Dorigo and Stützle, 2004), ABC algorithm (Karaboga and Basturk, 2007), bat algorithm (BA) (Yang and Gandomi, 2012), CS (Yang, 2009), PSO (Kennedy and Eberhart, 1995), harmony search (HS) (Lee and Geem, 2005), firefly algorithm (FA) (Yang, 2010), and krill herd algorithm (Gandomi and Alavi, 2012a) among others. MAs can be classified in different ways (Blum and Roli, 2003); however, in this chapter, we will focus on nature-inspired MAs [ref].

Metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity
Metaheuristic
Metaheuristic: Classes of Search Techniques
Metaheuristic: Classes of Search Techniques

███ Are Neural Networks Useful for Game AI? [Part 1] ███

Discussion: Are Neural Networks Useful for Game AI? [Part 1]

Alex J. Champandard on November 13, 2007: 
“Single- and multi-layer perceptrons trained using back-propagation have had the most practical success in games to date.”`

MarI/O - Machine Learning for Video Games
SethBling (Published on Jun 13, 2015):

MarI/O is a program made of neural networks and genetic algorithms that kicks butt at Super Mario World.
Source Code: http://pastebin.com/ZZmSNaHX
"NEAT" Paper: http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf
Some relevant Wikipedia links:
https://en.wikipedia.org/wiki/Neuroevolution
https://en.wikipedia.org/wiki/Evolutionary_algorithm
https://en.wikipedia.org/wiki/Artificial_neural_network
BizHawk Emulator: http://tasvideos.org/BizHawk.html






Saturday, February 13, 2016

Can one setup log-shipping between databases on the same SQL Server instance?

Can one setup log-shipping between databases on the same SQL Server instance?

Yes! One can setup logshipping between databases on the same SQL Server instance, however, the secondary database must have a different name.

Friday, February 5, 2016

Servo (layout engine)

Servo is an experimental web browser layout engine being developed by Mozilla Research, with Samsung porting it to Android and ARM processors. The prototype seeks to create a highly parallel environment, in which many components (such as rendering, layout, HTML parsing, image decoding, etc.) are handled by fine-grained, isolated tasks. The project has a symbiotic relationship with the Rust programming language, in which it is being developed.

Servo provides a consistent API for hosting the engine within other software. It is designed to be compatible with Chromium Embedded Framework, an API used by Adobe and Valve Corporation to incorporate the Blink rendering engine within their own products. Allowing Servo to be dropped in as a replacement engine simplifies real-world testing.

Two significant components used by Servo are based on pre-existing C++ code from Mozilla. JavaScript support is provided by SpiderMonkey, and the 2D graphics library Azure is used to interface to OpenGL and Direct3D.

Servo is named after Tom Servo, a robot from the television show Mystery Science Theater 3000.


https://en.wikipedia.org/wiki/Servo_(layout_engine)


SpiderMonkey

SpiderMonkey is the code name for the first-ever JavaScript engine, written by Brendan Eich at Netscape Communications, later released as open source and currently maintained by the Mozilla Foundation. SpiderMonkey provides JavaScript support for Mozilla Firefox and various embeddings such as the GNOME 3 desktop.
https://en.wikipedia.org/wiki/SpiderMonkey_(software)

DevOps

DevOps  

DevOps (a clipped compound of "development" and "operations") is a culture, movement or practice that emphasizes the collaboration and communication of both software developers and other information-technology (IT) professionals while automating the process of software delivery and infrastructure changes.It aims at establishing a culture and environment where building, testing, and releasing software, can happen rapidly, frequently, and more reliably. [more info]

███ Actor-Based Concurrency ███

Actor-Based Concurrency

The actor model in computer science is a mathematical model of concurrent computation that treats "actors" as the universal primitives of concurrent computation: in response to a message that it receives, an actor can make local decisions, create more actors, send more messages, and determine how to respond to the next message received. The actor model originated in 1973.[1] It has been used both as a framework for a theoretical understanding of computation and as the theoretical basis for several practical implementations of concurrent systems. The relationship of the model to other work is discussed in Indeterminacy in concurrent computation and Actor model and process calculi.[more info]

Example: Akka is an open-source toolkit and runtime simplifying the construction of concurrent and distributed applications on the JVM. Akka supports multiple programming models for concurrency, but it emphasizes actor-based concurrency, with inspiration drawn from Erlang.Language bindings exist for both Java and Scala. Akka is written in Scala and, as of Scala 2.10, Akka's actor implementation is included as part of the Scala standard library. [more info]

███ ABI (Application Binary Interface) ███

ABI (Application Binary Interface)

ABI is the interface between two program modules, one of which is often a library or operating system, at the level of machine code. [more info]





IT service management (ITSM)

IT service management (ITSM) 

IT service management (ITSM) refers to the entirety of activities – directed by policies, organized and structured in processes and supporting procedures – that are performed by an organization or part of an organization to plan, deliver, operate and control IT services offered to customers. It is thus concerned with the implementation of quality IT services that meet the needs of customers, and is performed by the IT service provider through an appropriate mix of people, process and information technology.

Differing from more technology-oriented IT management approaches like network management and IT systems management, IT service management is characterized by

  1.    adopting a process approach towards management
  2.    focusing on customer needs and IT services for customers rather than IT systems
  3.    stressing continual improvement
There is an international, chapter-based professional association, the IT Service Management Forum (itSMF). The main goal of the itSMF is to foster the exchange of experiences and ideas between users of ITSM frameworks. To this end, national itSMF chapters organize conferences and workshops. Some of them also contribute to the translations of ITSM framework documents into their respective languages or publish own ITSM guides.

IT service management (ITSM)
IT service management (ITSM)