NuTech Solutions, Inc.
Simulation and Evolution Work Well Together
Lawrence “David” DavisVP of Product Research
NuTech Solutions, Inc. Topics
Terminology What is simulation? What are evolutionary algorithms? Some Case studies:
Investigating contacts Target allocation Army/NASA cockpit procedures Interpreting data
Conclusions
NuTech Solutions, Inc. Terminology
Simulation Monte Carlo Simulation Evolutionary Algorithm Genetic Algorithm Heuristic Evaluation Procedure
NuTech Solutions, Inc. About Simulation
Simulation involves reproducing events at the level of detail we care about
Can be done at a fine level of detail (agent-based modeling)
Can be done at a higher level Often has unexpected outcomes Should include what we care
about and finesse the rest
NuTech Solutions, Inc.
Simulation: doesn’t change
Our strategy: Adapts
NuTech Solutions, Inc. Why Evaluate with Simulations?
Simulations represent interactions that we can’t capture in other ways
Highly detailed effects “Cascading” effects Probabilistic effects Statistical reports are possible
NuTech Solutions, Inc. What are Evolutionary Algorithms?
Genetic algorithms—evolution simulated on a computer
We “evolve” the solutions to hard problems instead of figuring them out
Good for problems where mathematical techniques can’t be applied
Good when we need a reasonable answer fairly quickly
Really good when used to find rule sets or strategies that do well under simulation
NuTech Solutions, Inc. Case Study:
Investigating Contacts
We have unidentified contacts in the ocean
We have different types of assets available (towed sensor arrays, underwater vehicles, rulees, etc)
When we have a contact, we want to allocate assets to investigate it
Success means determining what the source of the contact was, and continuing to monitor it if it interests us
NuTech Solutions, Inc. Investigating Contacts:
Features of the Problem
The area the contact could be in increases in size with time
Different assets may work well together or may hamper each other (underwater vehicles can hinder surface listening devices)
We need to be able to investigate other contacts if they occur, so we might not want to allocate all our assets to any one contact
NuTech Solutions, Inc. Features of the Simulation
We can model the arrival of contacts probabilistically
When contacts occur, they modify the probabilities of other contacts
When we learn about the contacts, this modifies our view of the probabilities
Some contacts don’t represent interesting things
Some contacts are extremely interesting
NuTech Solutions, Inc. We want to…
Find real contact sources at a high rate of success
Investigate multiple contacts with a high rate of success
Minimize cost of operations, and/or number of assets used
NuTech Solutions, Inc. What the Simulator is Like
The simulator generates events with probabilities based on our experience
It includes algorithms for computing success rates at finding event sources
It includes algorithms for changing the size of the search area with time
The simulator measurements of success are sensitive to weather, day/night, season, asset combinations, type of source, etc.
NuTech Solutions, Inc. What’s in the Simulator
A driver that steps us forward in time An event interpreter that creates events
based on the input probabilities Objects of various types that can
interact: assets, sources, weather events, and equipment
A statistics gatherer that tracks success rates and other data that interests us
NuTech Solutions, Inc. Example of a Simulator Event
There is currently an unidentified contact (a submarine) at location 1
Assets are allocated to investigate the contact, using the current allocation and search rules
The simulator knows the course of the submarine
The simulator increases the probability of other contacts related to this source along its course
If a source of this type generally travels alone, the probability of other contacts of its type is reduced for some time
NuTech Solutions, Inc. Another Example of
a Simulator Event There is currently an unidentified contact (a
fishing boat) at location 2 Assets are allocated to investigate the
contact, using the current allocation and search rules
The simulator knows the course of the fishing boat
The probability of other contacts related to the boat along its course is increased
The probability of identifying the type of source through radio and more detailed monitoring is computed
NuTech Solutions, Inc. Example Rules for Asset Allocation
“If no other contacts are live and this contact is within 200 miles of base, send the slow but sensitive assets to investigate”
“Don’t send towed arrays and underwater assets to investigate the same contact”
“If there are three contacts in a straight line, concentrate search in the area on the projection of that line”
NuTech Solutions, Inc. How to Get Good Rule Sets
Start with randomly-generated rule sets, or rule sets that represent human heuristics
Evolve better and better rule sets Simulate months or years of activity to
evaluate a rule set Use the desired features of the problem to
decide which are the good rule sets and which are the bad ones
Make more rule sets, but let the good ones proliferate more than the bad ones
Mutate and cross-breed rule sets
NuTech Solutions, Inc. The rule sets Get Better
The system, evolving rule sets that function well in the context of the simulator, produces a rule set that works well for the kinds of contacts we are simulating
Sometimes these rule sets can have unexpected features
Mathematical techniques aren’t well suited to find solutions in the context of simulations
Evolutionary algorithms are very well suited for finding good procedures under evaluation by simulators
NuTech Solutions, Inc. Case Study: Target Allocation
Suppose you have a force faced with a group of approaching unfriendly objects
How should you allocate fire in order to achieve your goals?
Early decisions influence later ones Important targets should receive more
attention Some interactions between weapon types
are important: visual interference Distance effects matter, as does target
change time, etc
NuTech Solutions, Inc. How to Evaluate a
Target Allocation Strategy
Important targets have a high probability of being eliminated
Low probability of elimination of our force members
Minimize duration of interaction Minimize expenditure of ammunition Minimize loss of crew
NuTech Solutions, Inc. Target Allocation is Similar to
Contact Investigation
This problem can be handled just like investigating contacts, except that the contacts are all considered at the same time
A simulation of the interaction is a good way to evaluate a blend of weaponry and a targeting strategy
An evolutionary algorithm can be used to find good target allocation rule sets
NuTech Solutions, Inc. Different Rule Sets for Different
Types of Engagements Targets are aircraft Targets are boats Targets are mixed types Targets are far away and of unknown types We are moving We have time constraints
NuTech Solutions, Inc. Example Rules for Target Allocation
(rule for one type of gun) Target the incoming object with the highest combination of importance and residual hit probability
(low visibility) Switch targets when probability of kill of the current target is greater than 96%
Target the guns with the highest probability of kills first
NuTech Solutions, Inc. Evolve Good Rule Sets
Evolve a high-performance rule set by putting each candidate through a very large number of simulated engagements of the expected types, weighted by probability
Evolve rule sets for different types of engagements by starting a different evolutionary process for each type, and creating rule sets that function well for that type of engagement
Evolve different rule sets depending on the objectives: high survivability, high kill rate, deterrence, interdiction, etc.
NuTech Solutions, Inc. Case Study: NASA in-cockpit
Procedures Studies
A3I project (Army-NASA Aircrew Aircraft Integration)
Also called MIDAS Simulated the effects of required
procedures on cockpit crews (commercial aircraft and Apache helicopter crews)
For commercial crews, simulated cockpit information systems and their effect in normal and emergency situations
For helicopter crews, simulated effectiveness of mission procedures
NuTech Solutions, Inc. Example of a Simulator Event
There is a truck convoy ahead Two helicopters are assigned to locate it and
deliver a missile strike Pop-up and jinking procedures are used to
do reconnaissance and evasion of ground-to-air missiles
One pilot locates the target for the other Radio procedures, cognitive procedures, and
situational awareness are modeled Simulation is critical in assessing the impact
of different equipment and mission strategies
NuTech Solutions, Inc. Evolution can be Used to Find Good
Strategies and Displays
Measure pilot effectiveness through hundreds of thousands of mission simulations to find the best strategies
Evolve cockpit displays to find those that give the highest levels of performance across hundreds of thousands of mission simulations
System used with minor modifications for police emergency call stations and astronaut repair missions
NuTech Solutions, Inc. Case Study:
Interpreting Data
We get LOFARgrams from listening apparatus
Some contacts may be whales or fishing boats
Some may be large metallic fish Human experts can interpret the signals
with high accuracy Humans tend to be best in the region and
conditions where they were trained—Pacific, no storms, no whales in background, etc
NuTech Solutions, Inc. The Task
Produce an expert system that can do what the humans do
Big difficulty: identifying visual patterns that the humans see easily (“lines” in the data)
Expert system techniques didn’t produce good results at line-tracing
Development team used a genetic algorithm
NuTech Solutions, Inc. How the Algorithm Worked
Hundreds of LOFARgrams were marked by humans so that the interesting lines were identified
The genetic algorithm evolved rule sets for interpreting the data
A rule was evaluated based on how well it matched the human analysis
Over time, the system learned to do this as well as humans
By changing the training cases, the system could learn to do this in different locations, conditions, and types of background noise
NuTech Solutions, Inc. Terminology
Simulation Monte Carlo Simulation Evolutionary Algorithm Genetic Algorithm Heuristic Evaluation Procedure
NuTech Solutions, Inc.
Simulation: Strategies adapt
Our strategy: Fixed
A Useful Extension
NuTech Solutions, Inc. Conclusions
Simulations can be more accurate and informative than high-level or mathematical models of an event
Probabilistic simulations show us what can happen under a wide variety of conditions
Many interesting problems can be solved very well if we simulate, evaluate, and evolve
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