SPOT - Sequential Parameter Optimization Toolbox

Release Notes Version 1.0.2662
	Removed the dependency on the maptree package, changed the corresponding default report function spotReportDefault

Release Notes Version 1.0.2661
	1. Significant speedup for spotPredictForrester, by factors of 2 or more (depending on dimensionality and number of observations)
	2. Fix in spotPredictForrester: Sometimes L-BFGS-B might violate boundaries, this is now checked and controlled by the calling function
	3. Better coloring in 3d plots (spotReport3d), both surface plot reports (spotReport3d and spotReportContour) use the same color scheme.
	4. Bugfix when using OCBA: RNG seeds are now determined in the right order
	5. Multi criteria optimization with SPOT now uses a more appropriate infill criterion: When estimating the hypervolume contribution of points suggested by a model, allready known points will also be considered.
	6. The Evolutionary Strategy used as a target algorithm for SPOT can now be called with an optim-like interface: esOptim
	7. For stability reasons, the nugget effect in the kriging model spotPredictDice is now always on.
	
Release Notes Version 1.0.2257
	Version has changed from 0.1.* to 1.0.*, since now one of the most
	important predictors from the original Matlab package is implemented, 
	as well	as methods for Multi Criteria Optimization.
	More detailed changes are:
	1. Fixed auto.loop.nevals stopping criterion (one superfluous step)
	2. Added several additional examples of surrogate model interfaces: 
		spotPredictForrester (new, more stable Kriging model,
			based on forrester code as used with original Matlab-SPOT)
		spotPredictEarth (MARS, based on earth package)
		spotPredictGausspr (based on kernlab package gausspr)
		spotPredictKsvm (SVM based on kernlab package)
		spotPredictPsvm (Penalized SVM)
		spotPredictQrnn (Quantile regression neural network, from qrnn package) 
	3. Adaptions for R 2.14.X (Namespace and others)
	4. Dependencies changed, removed unused dependencies, moved optional 
		dependencies to suggests
	6. MSPOT: Spot can now do multi criteria optimization, see also 
		vignette("MultiCriteriaSPOT").
	7. Updated some demos to use new and better features
	9. Changed default settings in SANN and ES algorithm interfaces
	10. Bugfix to seed handling in target algorithm/function interfaces: 
		Will now be saved and loaded to make sure that seed of main SPOT 
		processes is undisturbed.
	11. spotPredictMlegp can be run with limited number of observations 
		(randomly sampled), to prevent exploding time consumption
	12. Documentation updated
	14. New demo for tuning symbolic regression (RGP)
	15. New report functions which create surface plots: 
		spotReport3d, spotReportContour
	16. Changes to spotGetOptions and related functions:
		- any .path variables in the spotConfig were removed. User should 
			make sure to load function to workspace.
		- Removed unused parameter settings
		- Settings of optional modules/functions will now be handled in 
			those very functions, not in spotGetOptions. That means, they 
			will only be in the list of parameters if actually used or 
			set by the user.
	17. Region of Interest will now use lower/upper instead of low/high 
		for column names of boundaries. A new constructor can be used to 
		create Region Of Interests: spotROI
	18. Some internal functions now use single arguments instead of 
		parameter list (spotWriteDes, spotWriteAroi, spotReadRoi)
	19. Updated the spotGui() function to fit to the changes (new version: 1.3)
	20. spot() and spotOptim() have now the argument "..." (dot-dot-dot) to 
		pass on additional parameters to a target function.

	
Release Notes Version 0.1.1550
	1. Fixed bugs with regard to problems with handling random number generator seed
	2. Changes to spotTask "meta" (spotStepMetaOpt): New structure, not fully documented yet.
	3. Sensitivity report will not use the same graphic window as the online plot anymore
	4. Changed/added suitable error messages
	3. some other smaller bug fixes
	
	
Release Notes Version 0.1.1375
	1. Important new function: 
		spotOptim: an optim like spot interface
		spotOcba: used with spotCreateSequentialDesignOcba. It is the new default, 
				but works only with noisy functions. See documentation. 
	2. Prediction functions should now return spotConfig. Both the model fit 
		(if available, used for the predict interface) and the y values 
		for the large design are returned inside spotConfig.
	3. Any model fit that works with the predict interface can now be optimized in 
		a additional function call in the sequential design step.
		Therefore a new parameter is introduced: spotConfig$seq.predictionOpt.func
		See also: spotPredictOptMulti
	4. Usabillity changes to the spotGui
	5. Updated documentation 
	6. Setting spot.seed or alg.seed to NULL will result into randomly chosen seeds.
	7. spot() and spotOptim() can be started without file input or output.
	8. New test functions
		spotFuncStartMexicanHat
		spotFuncStartRastrigin
		spotFuncStartRosenbrock
	9. Function handles can be passed to spot or spotOptim, instead of strings, for 
		the used objective function.
	10. readded to the package spotPredictKrig
	11. several bugfixes to predictors and other functions
	12. Where possible, verbosity of other packages used by spot is now in line with spot's verbosity
	
	Known major problems:
	spotpredictLmOptim does not work with interface changes (this also affects the corresponding demo)
		
	
Release Notes Version 0.1.1065
	1. New parameters in spotConfig:
		a.	spot.fileMode: Boolean, defines if 
			created data is logged in res/des/bst/aroi files
			If TRUE (default) files will be written, else
			the results will be written to spotConfig (see
			the followind parameters)
		b.	alg.currentResult: Holds the results of the
			target algorithm or function that is optimized 
			by spot, as a data frame. (earlier only in .res file)
		c.	alg.aroi: this holds the aroi (earlier only in .aroi 
			file)
		d.	alg.currentBest: This holds a data frame with the best
			results (earlier only in .bst files)
		e.	alg.currentDesign: This holds a data frame with the 
			design to be evaluated by the next \"run\" task.(earlier
			only in .des files)

	2. Changes to userdefined functions:

		spotConfig$alg.func:
		This function now recieves and returns only spotConfig.
		This means resFileName, apdFileName, and desFileName are no
		input arguments anymore, they need to be read from 	spotConfig.
		The function needs to be changed to write the \"result\" data
		frame to the spotConfig$alg.currentResult.
		It can also be written to .res file, if wanted by the user.
		(check for spotConfig$spot.fileMode if needed)

		spotConfig$report.func
		The function now also returns spotConfig.
		To get the best value the following lines are be used now in the default report: 
		#################################	
		spotConfig=spotWriteBest(mergedData, spotConfig);
		C1=spotConfig$alg.currentBest[nrow(spotConfig$alg.currentBest),]
		#################################

		In general some spot functions you might use in your
		userdefined functions will now return spotConfig.

	3. spot() can now be called with a list of settings, e.g. spotConfig.
		example: spot(\"example.conf\",\"auto\",spotConfig=list(auto.loop.nevals=150)).
		spot() will also return the spotConfig. This can then be feed into the next spot() run.

	4. Changes to the spotGui:
		a.	The spotGui layout was changed, a menu bar added.
		b.	New feature: Create your own test functions with
		the function generator

		
Release Notes Version 0.1.1016:
	1. New function: spotGui()
		Starts a java gui to work with SPOT
	2. New parameters for the \"meta\" task:
		- spotConfig$report.meta.func
		- spotConfig$report.meta.path
		Define name and path of a report that summarizes a meta experiment
	3. Fixed Documentation

	
Initial version: 0.1.888
