Couple of weeks ago, in May, 2017, I gave a guest lecture at Faculty of Kinesiology at Zagreb University in Croatia, thanks to the invitation by Cvita Gregov. The topic of my talk was Agile Periodization, a framework that I have been developing over the past few years. Since I already had the slides ready, I slightly modified them and decided to record the whole thing in English - http://tinyurl.com/klzexpt

1. Agile Periodization
Decision making under Uncertainty
Mladen Jovanović

3. ...So it might come as a surprise that this is not what modern computers are
actually doing when they face a difficult problem. Straightforward arithmetic,
of course, isn’t particularly challenging for a modern computer. Rather, it’s
tasks like conversing with people, fixing a corrupted file, or winning a game
of Go—problems where the rules aren’t clear, some of the required
information is missing, or finding exactly the right answer would require
considering an astronomical number of possibilities—that now pose the
biggest challenges in computer science. And the algorithms that researchers
have developed to solve the hardest classes of problems have moved
computers away from an extreme reliance on exhaustive calculation.
Instead, tackling real-world tasks requires being comfortable with chance,
trading off time with accuracy, and using approximations.
...Even where perfect algorithms haven’t been found, however, the battle
between generations of computer scientists and the most intractable real-
world problems has yielded a series of insights. These hard-won precepts
are at odds with our intuitions about rationality, and they don’t sound
anything like the narrow prescriptions of a mathematician trying to force the
world into clean, formal lines. They say: Don’t always consider all your
options. Don’t necessarily go for the outcome that seems best every time.
Make a mess on occasion. Travel light. Let things wait. Trust your instincts
and don’t think too long. Relax. Toss a coin. Forgive, but don’t forget. To
thine own self be true.

4. Planning?

5. Planning?

6. Planning?

7. Planning?

8. • Hierarchy
• Goal/Method
• Predictability
• Waterfall
• Top-down
WUT?!?!

9. Hierarchy

10. Hierarchy

11. Hierarchy

12. Hierarchy

13. Hierarchy

14. Hierarchy
Biomotor abilities Technical skills

15. Hierarchy

16. Goal/Method

17. Goal/Method

18. Goal/Method

19. Goal/Method

20. Goal/Method

21. Goal/Method

22. Predictability

23. Predictability

24. Predictability

25. Predictability

26. Waterfall

27. Waterfall

28. Waterfall

29. Top-Down

30. Top-Down

31. Top-Down

34. Agile approach

35. • Iterative planning
• MVP
• Barbell Strategy
• Embedded testing
• Transparency
• Randomize
• Heuristics

36. Iterativeplanning

37. Iterativeplanning

38. Iterativeplanning

39. Iterativeplanning

40. Iterativeplanning

41. Iterativeplanning

42. MVP

43. MVP

44. MVP

45. Heuristics
Physical potential
(MAS, V02max...)
Game
performance

46. Heuristics • 1/N heuristic
• Micro-loading
• If important do it every day
• First things first
• Barbell strategy
Reduce N
• Alternate/Randomize
• Read Dan John

47. Barbellstrategy
Mixed-
Parallel
Uni-
directi
onal

48. Barbellstrategy

49. Barbellstrategy

50. Embeddedtesting

51. Transparency

52. Transparency

53. Randomize For most of Western history, chance has been a villain. In
classic Roman civilization, chance was personified by
Fortuna, goddess of cruel fate, with her spinning wheel of
luck. Opposed to her sat Minerva, goddess of wisdom and
understanding. Only the desperate would pray to Fortuna,
while everyone implored Minerva for aid. Certainly science
was the domain of Minerva, a realm with no useful role for
Fortuna to play.
But by the beginning of the 20th century, the opposition
between Fortuna and Minerva had changed to a
collaboration. Scientists, servants of Minerva, began
publishing books of random numbers, instruments of chance
to be used for learning about the world. Now, chance and
wisdom share a cooperative relationship, and few of us are
any longer bewildered by the notion that an understanding of
chance could help us acquire wisdom. Everything from
weather forecasting to finance to evolutionary biology is
dominated by the study of stochastic processes

54. Randomize Chapter 10 showed, with the illustration of
Buridan’s donkey, that randomness is not always
unwelcome. This discussion aims to show how
some degree on unpredictability (or lack of
knowledge) can be beneficial to our defective
species. A slightly random schedule prevents us
from optimizing and being exceedingly efficient,
particularly in the wrong things. This little bit of
uncertainty might make the dinner relax and forget
the time pressures. He would be forced to act as a
satisficer instead of maximizer (Chapter 11
discussed Simon’s satisficing as a blend of
satisfying and maximizing) – research on
happiness shows that those who live under the
self-imposed pressure to be optimal in their
enjoyment of things suffer a measure of distress

55. Randomize

56. Randomize

57. Randomize