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---
id: 20251223161108
title: Andre Platzer
type: permanent
created: 2025-12-23T21:11:08Z
modified: 2025-12-23T21:53:21Z
tags: []
---
# Andre Platzer
Andre Platzer is a computer scientist who is a professor at
both Carnegie Mellon and the Karlsruhe Institute of
Technology. Platzer is a leading researcher in
[[differential dynamic logic]] and [[cyber-physical
systems]]. He has helped to create
software like [[KeYmaera X]].
He has also written a book, called "Logical Foundations of
Cyber-Physical Systems." Manyu worked with KeYmaera X some
and was inspired by his work.

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id: 20251223162450
title: Web of Science
type: permanent
created: 2025-12-23T21:24:50Z
modified: 2025-12-23T21:29:48Z
tags: []
---
# Web of Science
Web of Science is a citation aggregator and database. Web of
Science has both forward and backward citation sources, and
other tools for doing source analysis. It is good to find
resources, but also to connect resources to one another.
This is useful in [[snowballing]].

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id: 20251223162954
title: Snowballing
type: permanent
created: 2025-12-23T21:29:54Z
modified: 2025-12-23T21:31:23Z
tags: []
---
# Snowballing
Snowballing is a form of source discovery. Snowballing means
to start with a source, and travel forwards and backwards
in time with respect to citations. From this, one can find
closely related papers to an original source without too
much effort.
Snowballing has been found in the literature to be an
efficient source of collecting relevant sources given a
certain topic. One needs to find the first bit of snow (a
good first resource), to start the snowball.

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---
id: 20251223163648
title: Deterministic Parity Automata
type: permanent
created: 2025-12-23T21:36:48Z
modified: 2025-12-23T21:40:09Z
tags: []
---
# Deterministic Parity Automata
Deterministic parity automata are a type of automata where
the environment and the system play against one another, and
describes the interactions therein. DPA are exhaustive, and
end up with a result determining which player 'wins'.
DPA's have a scoring mechanism that results in an even or
odd final score. An even final score indicates that the
'controller' wins the game. There is no input from the
environment that can't be controlled by the controller. All
traces end up in a favorable state, with no infinite loops.
An odd score means the opposite. There exists some limit
cycle where the controller can't reach a desired mode and
stay there.
DPA's are used in [[strix]]. They're how Strix does it's
generation from temporal logics to a final automaton.

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---
id: 20251223165340
title: Mealy Machines
type: permanent
created: 2025-12-23T21:53:40Z
modified: 2025-12-23T22:38:18Z
tags: []
---
# Mealy Machines
Mealy machines are a formalization of a system that has
states drawn as nodes and transitions drawn from state to
state.
From Wikipedia:
```
A mealy machine is a finite state machine whose
output values are determined by both its current state, and
the current inputs.
```
Mealy machines can also be defined as a six-tuple:
$$(S, S_0, \Sigma, \Lambda, T, G)$$
where
- S is the finite set of states
- S_0 is the start state
- $\Sigma$ is the input alphabet
- $\Lambda$ is the output alphabet
- $T : S \times \Sigma \rightarrow S$ is the state
transition function
- $G : S \times \Sigma \rightarrow \Lambda$ is the output
function
Mealy machines have the advantage that they generally can
produce smaller sized automata (aka less states). This is
because transitions themselves in a Mealy machine are states
in a Moore machine. The state of 'opening' in a Moore
machine is the transition itself in a Mealy machine. Outputs
aren't just based on state, so it isn't necesary to create a
state to produce an output like a Moore machine. An output
action can be created with the current state AND the input
together.
## Related
[[Finite State Machines]]

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---
id: 20251223170627
title: Finite State Machines
type: permanent
created: 2025-12-23T22:06:27Z
modified: 2025-12-23T22:39:00Z
tags: []
---
# Finite State Machines
Finite State Machines are a computer science term for
machines that have a finite number of states, with clearly
defined transitions between them. Sometimes, FSM are
referred to simply as *state machines*.
FSM are an abstraction of a computational system. FSM are
heavily used in systems that have clearly defined discrete
states. Examples include traffic lights, elevators,
combination locks, or others.
FSM have **actions**. Actions are the unabstractified
version of whatever the execution is. For physical systems,
it might be something like turning a motor on.
FSM can be categorized into two main categories:
## Acceptors (or 'detectors' or 'recognizers') Acceptors are
a type of FSM that produce binary output, recognizing
whether or not a given input is accepted. Examples of
systems that are acceptors include things like ready-commit
systems, or a password checker. These systems have an input,
and reach a state that determines the input is acceptable,
or incorrect.
## Transducers
Transducers are a set of finite state machines that produce
an output based on input or state using *actions*. Actions
in this case represent a transition between state that
also has some external change. A finite state machine of an
elevator would have actions of the elevator changing between
floors, for example.
Transducers with respect to control have two different
types:
[[mealy-machines]] -- these have output depend on state and input
[[moore-machines]] -- these have output depend on state ONLY

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---
id: 20251223171835
title: Moore Machines
type: permanent
created: 2025-12-23T22:18:35Z
modified: 2025-12-23T22:39:56Z
tags: []
---
# Moore Machines
Moore machines are a type of finite state machine whose
output only depends on output state. Moore machines are
useful because they simplify the behavior of a system to the
simplest behaviours possible. They can be defined as a
six-tuple:
$$(S, S_0, \Sigma, \Lambda, T, G)$$
where
- S is the finite set of states
- S_0 is the start state
- $\Sigma$ is the input alphabet
- $\Lambda$ is the output alphabet
- $T : S \times \Sigma \rightarrow S$ is the state
transition function
- $G : S \rightarrow \Lambda$ is the output
function
Moore machines do not have exit actions. They can only
change their output based on a change of state. This means
for systems with physical characteristics, such as a door
opening or closing system, the intermediate states of
opening and closing have to exist in a Moore machine. It is
not possible to go from Open to Closed directly, because
Open can't generate the output Closed. Instead, Open + the
input 'open_door' or similar goes to the state 'closing',
which can then create an action of 'motor_on' or similar,
and then finally get to the final state Closed.